Sentiment Analysis & Dialog Systems 2017


Notes:

The number of academic papers covering both sentiment analysis and dialog systems continues to go up year on year, from 2015 to 2017.

Wikipedia:

Reference:

See also:

100 Best Sentiment Analysis Videos | Affective Dialog SystemsAffect Listener & Dialog Systems | Sentiment Analysis Tools (Open Source) & Dialog Systems


A practical guide to sentiment analysis
E Cambria, D Das, S Bandyopadhyay, A Feraco – 2017 – Springer
… manifestations of affect (facial expressions, posture, behavior, physiology), and affective interfaces and applications (dialogue systems, games, learning etc … Erik Cambria• Dipankar Das Sivaji Bandyopadhyay• Antonio Feraco Editors A Practical Guide to Sentiment Analysis 123 …

Ensemble application of convolutional neural networks and multiple kernel learning for multimodal sentiment analysis
S Poria, H Peng, A Hussain, N Howard, E Cambria – Neurocomputing, 2017 – Elsevier
… Elsevier. Neurocomputing. Volume 261, 25 October 2017, Pages 217-230. Neurocomputing. Ensemble application of convolutional neural networks and multiple kernel learning for multimodal sentiment analysis … 3.1. Text based emotion and sentiment analysis …

Topic independent identification of agreement and disagreement in social media dialogue
A Misra, M Walker – arXiv preprint arXiv:1709.00661, 2017 – arxiv.org
… Topic Independent Identification of Agreement and Disagreement in Social Media Dialogue Amita Misra & Marilyn A. Walker Natural Language and Dialogue Systems Lab Computer Science Department University of California, Santa Cruz maw|amitamisra@soe.ucsc.edu …

Really? well. apparently bootstrapping improves the performance of sarcasm and nastiness classifiers for online dialogue
S Lukin, M Walker – arXiv preprint arXiv:1708.08572, 2017 – arxiv.org
… Well. Apparently Bootstrapping Improves the Performance of Sarcasm and Nastiness Classifiers for Online Dialogue Stephanie Lukin Natural Language and Dialogue Systems University of California, Santa Cruz 1156 High Street, Santa Cruz, CA 95064 slukin@soe.ucsc.edu …

Adversarial learning for neural dialogue generation
J Li, W Monroe, T Shi, A Ritter, D Jurafsky – arXiv preprint arXiv …, 2017 – arxiv.org
… generation and music generation. Outside of sequence generation, Chen et al. (2016b) apply the idea of adversar- ial training to sentiment analysis and Zhang et al. (2017) apply the idea to domain adaptation tasks. Our work is …

Using Summarization to Discover Argument Facets in Online Ideological Dialog
A Misra, P Anand, JEF Tree, M Walker – arXiv preprint arXiv:1709.00662, 2017 – arxiv.org
… c 2015 Association for Computational Linguistics Using Summarization to Discover Argument Facets in Online Idealogical Dialog Amita Misra, Pranav Anand, Jean Fox Tree, and Marilyn Walker UC Santa Cruz Natural Language and Dialogue Systems Lab 1156 N. High …

Automatic sarcasm detection: A survey
A Joshi, P Bhattacharyya, MJ Carman – ACM Computing Surveys (CSUR …, 2017 – dl.acm.org
… This is a crucial step to sentiment analysis, considering prevalence and challenges of sarcasm in sentiment-bearing text … CCS Concepts: • Information systems ? Sentiment analysis; • Computing methodologies ? Natural language processing; …

Data-driven dialogue systems for social agents
KK Bowden, S Oraby, A Misra, J Wu, S Lukin – arXiv preprint arXiv …, 2017 – arxiv.org
… transformations [3]. Of course, while many data sources may be of interest for indexing knowledge for a dialogue system, annotations are … data-driven methods to repurpose existing social media dialogues, in addition to a suite of tools for sentiment analysis, topic identification …

Variational Autoencoder for Semi-Supervised Text Classification.
W Xu, H Sun, C Deng, Y Tan – AAAI, 2017 – aaai.org
Page 1. Variational Autoencoder for Semi-Supervised Text Classification Weidi Xu, Haoze Sun, Chao Deng, Ying Tan Key Laboratory of Machine Perception (Ministry of Education), School of Electronics Engineering and Computer …

How to make context more useful? an empirical study on context-aware neural conversational models
Z Tian, R Yan, L Mou, Y Song, Y Feng… – Proceedings of the 55th …, 2017 – aclweb.org
… RQ2. What is the effect of context on neural dialog systems? We … per. Such method is also used in other NLP tasks, eg, document-level sentiment analysis (Xu et al., 2016) and machine comprehension (Wang and Jiang, 2017) …

Convolutional neural networks for multi-topic dialog state tracking
H Shi, T Ushio, M Endo, K Yamagami… – Dialogues with Social …, 2017 – Springer
… to classify sentences [3]. It has been shown that this CNN model improves state of the art performance on several major text classification tasks including sentiment analysis and question … 1. Lemon, O., Pietquin, O.: Data-Driven Methods for Adaptive Spoken Dialogue Systems …

Affect-lm: A neural language model for customizable affective text generation
S Ghosh, M Chollet, E Laksana, LP Morency… – arXiv preprint arXiv …, 2017 – arxiv.org
… The automated processing of affect in human verbal communication is of great importance to understanding spoken language sys- tems, particularly for emerging applications such as dialogue systems and conversational agents …

Augmenting end-to-end dialog systems with commonsense knowledge
T Young, E Cambria, I Chaturvedi, M Huang… – arXiv preprint arXiv …, 2017 – arxiv.org
… base for cognition-driven sentiment analysis. In Twenty-eighth AAAI conference on artificial intelligence. Dodge, J.; Gane, A.; Zhang, X.; Bordes, A.; Chopra, S.; Miller, A.; Szlam, A.; and Weston, J. 2015. Evaluating pre- requisite qualities for learning end-to-end dialog systems …

Learning lexico-functional patterns for first-person affect
L Reed, J Wu, S Oraby, P Anand, M Walker – arXiv preprint arXiv …, 2017 – arxiv.org
… Although Au- toSlog itself does not perform highly, the patterns that it learns represent a different type of knowl- edge than what is contained in many sentiment analysis tools … 2017. Data-driven dialogue systems for social agents …

Challenges in sentiment analysis
SM Mohammad – A Practical Guide to Sentiment Analysis, 2017 – Springer
… dialogue systems (Velásquez 1997; Ravaja et al. 2006). The sheer volume of work in this area precludes detailed summarization here. Nonetheless, it should be noted that often the desired application can help direct certain design choices in the sentiment analysis system …

Recent trends in deep learning based natural language processing
T Young, D Hazarika, S Poria, E Cambria – arXiv preprint arXiv …, 2017 – arxiv.org
… of natural language related tasks at all levels, ranging from parsing and part-of-speech (POS) tagging, to machine translation and dialog systems … almost the same embed- ding (Socher et al., 2011b), which is problematic if used in tasks such as sentiment analysis (Wang et al …

A roadmap for natural language processing research in information systems
D Liu, Y Li, MA Thomas – … of the 50th …, 2017 – hl-128-171-57-22.library.manoa …
… concerns the refinement and application of NLP techniques to solve real-world problems [3], such as creating spoken dialogue systems [4], speech-to … 16 6.69% 3 Text mining 15 6.28% 4 Information extraction 11 4.60% 5 Machine learning 10 4.18% 6 Sentiment analysis 9 3.77 …

Opinion Mining and Sentiment Analysis
E Breck, C Cardie – The Oxford Handbook of Computational …, 2017 – oxfordhandbooks.com
Opinions are ubiquitous in text, and readers of online text—from consumers to sports fans to news addicts to governments—can benefit from automatic methods that synthesize useful opinion-oriented information from the sea of data. In this chapter on opinion mining and sentiment …

Learning utterance-level representations for speech emotion and age/gender recognition using deep neural networks
ZQ Wang, I Tashev – Acoustics, Speech and Signal Processing …, 2017 – ieeexplore.ieee.org
… is becoming more and more important for many applications related to human computer interactions, especially for spoken dialogue systems … action or gesture recognition in videos [1], speaker identification in speech [2], and text categorization or sentiment analysis in natural …

Annotating and modeling empathy in spoken conversations
F Alam, M Danieli, G Riccardi – Computer Speech & Language, 2017 – Elsevier
… acoustic information. 2.2.2. Research on Sentiment Analysis from Text. When it comes to the term “Sentiment Analysis” current state-of-art research are mostly focused on extracting it from textual information (Pang et al., 2008). It …

Speech Intention Classification with Multimodal Deep Learning
Y Gu, X Li, S Chen, J Zhang, I Marsic – Canadian Conference on Artificial …, 2017 – Springer
… for dialog systems with Microsoft language understanding intelligent service (LUIS). In: Proceedings of 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue (2015)Google Scholar. 8. Pang, B., Lee, L.: Opinion mining and sentiment analysis. Found …

Predicting emotional word ratings using distributional representations and signed clustering
J Sedoc, D Preo?iuc-Pietro, L Ungar – … of the 15th Conference of the …, 2017 – aclweb.org
… Inferring the emotional content of words is important for text-based sentiment anal- ysis, dialogue systems and psycholinguis- tics, but word … Our method can assist building word ratings for new languages and improve down- stream tasks such as sentiment analysis and emotion …

RubyStar: A Non-Task-Oriented Mixture Model Dialog System
H Liu, T Lin, H Sun, W Lin, CW Chang, T Zhong… – arXiv preprint arXiv …, 2017 – arxiv.org
… The implicit goal of an open-domain non-task-oriented dialog system is to generate a coherent, pleasant and engaging conversation … the flow of conversation over successive contexts, including but not limited to: (i) using coreference resolution and sentiment analysis to achieve …

Harnessing cognitive features for sarcasm detection
A Mishra, D Kanojia, S Nagar, K Dey… – arXiv preprint arXiv …, 2017 – arxiv.org
… human readers. Sarcasm detec- tion has been a challenging research prob- lem, and its importance for NLP applica- tions such as review summarization, dia- log systems and sentiment analysis is well recognized. Sarcasm …

Navigation-orientated natural spoken language understanding for intelligent vehicle dialogue
Y Zheng, Y Liu, JHL Hansen – Intelligent Vehicles Symposium …, 2017 – ieeexplore.ieee.org
… For the navigation dialogue systems, it is desired to understand a driver’s spoken language in a natural way … The NLP stage is based on a Deep Neural Network (DNN) framework, which contains sentence-level sentiment analysis and word/phrase- level context extraction …

Controllable text generation
Z Hu, Z Yang, X Liang, R Salakhutdinov… – arXiv preprint arXiv …, 2017 – arxiv.org
Page 1. Controllable Text Generation ZhitingHu, ZichaoYang, XiaodanLiang, RuslanSalakhutdinov, EricP.Xing School of Computer Science, Carnegie Mellon University {zhitingh,zichaoy,xiaodan1,rsalakhu,epxing}@cs.cmu.edu Abstract …

Method for aspect-based sentiment annotation using rhetorical analysis
? Augustyniak, K Rajda, T Kajdanowicz – Asian Conference on Intelligent …, 2017 – Springer
… Wang, B., Liu, M.: Deep learning for aspect-based sentiment analysis, pp. 1–9 (2015)Google Scholar. 21. Wen, TH., Gasic, M., Mrksic, N., Su, PH., Vandyke, D., Young, S.: Semantically conditioned LSTM-based natural language generation for spoken dialogue systems …

Natural language processing
K Sirts – 2017 – courses.cs.ut.ee
… Lexical semantics • Information extraction • Text classification • Sentiment analysis • Information retrieval • Machine translation • Natural language generation • Text summarization • Dialog systems 23 Page 24. The general plan • A matrix of tasks and methods Tasks Classical …

Zooming in: studying collective emotions with interactive affective systems
M Skowron, S Rank, D Garcia, JA Ho?yst – Cyberemotions, 2017 – Springer
… The third study proved a successful application of the dialog system for eliciting social sharing of emotion and for realizing a communication scenario of ‘getting acquainted’ … 14.6.2.2 Emotional Persistence. Sentiment analysis techniques like the ones described in Chap …

Addressing challenges in promoting healthy lifestyles: the al-chatbot approach
A Fadhil, S Gabrielli – Proceedings of the 11th EAI International …, 2017 – dl.acm.org
… Future work is still needed to advance the Artificial Intelligence techniques required to obtain intelligent chatbot solutions for the healthcare domain, especially in terms of machine learning components, sentiment analysis and intent … “Anna: A Nutrition-Facts Dialogue System.”

Crystalnest at semeval-2017 task 4: Using sarcasm detection for enhancing sentiment classification and quantification
RK Gupta, Y Yang – Proceedings of the 11th International Workshop on …, 2017 – aclweb.org
… 2006. yeah right: sarcasm recognition for spoken dialogue systems. INTERSPEECH pages 1838–1841 … 2015. Ecnu: Multi-level sentiment analysis on twitter us- ning traditional linguistic features and word embed- ding features. SemEval pages 561–567 …

Deep Learning in Natural Language Processing
L Deng, Y Liu – 2017 – pdfs.semanticscholar.org
Page 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056 Volume: 04 Issue: 11 | Nov -2017 www.irjet.net p-ISSN:2395-0072 © 2017, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 930 …

Deconvolutional paragraph representation learning
Y Zhang, D Shen, G Wang, Z Gan… – Advances in Neural …, 2017 – papers.nips.cc
… paragraphs. These representations are typically a required first step toward more applied tasks, such as sentiment analysis [1, 2, 3, 4], machine translation [5, 6, 7], dialogue systems [8, 9, 10] and text summarization [11, 12, 13] …

Detection of Sarcasm in Text Data using Deep Convolutional Neural Networks
P Mehndiratta, S Sachdeva, D Soni – Scalable Computing: Practice and …, 2017 – scpe.org
… In AAAI (Vol. 11, pp. 1770-1771) [5] Tepperman, J., Traum, TR, and Narayanan, S. ” yeah right”: sarcasm recognition for spoken dialogue systems.. In INTERSPEECH … Investigating the Impact of Sarcasm on Sentiment Analysis. In LREC (pp. 4238-4243), (2014) …

An agent-based modeling framework for online collective emotions
D Garcia, A Garas, F Schweitzer – Cyberemotions, 2017 – Springer
… that cover a large variety of states, and these states evolve smoothly in time according to two principles: sentiment analysis from the … Dialog systems, more commonly known because of the use of chatbots, benefit from this framework, as agent-based models can be formulated as …

The chatbot feels you-a counseling service using emotional response generation
D Lee, KJ Oh, HJ Choi – Big Data and Smart Computing …, 2017 – ieeexplore.ieee.org
… Our purpose is developing a user sensitive dialog system that can comunnicate user over time with continuous contextual self-awareness through … Wöllmer, F. Weninger, T. Knaup, B. Schuller, C. Sun, K. Sagae, and LP Morency, “Youtube movie reviews: Sentiment analysis in an …

Robust Task Clustering for Deep Many-Task Learning
M Yu, X Guo, J Yi, S Chang, S Potdar… – arXiv preprint arXiv …, 2017 – arxiv.org
… 2. Diverse Real-World Tasks: User Intent Classification for Dialog System The second dataset is from an on-line service which trains and serves intent classification models to various clients … 5In conversational dialog systems, intent-labels are used to guide the dialog-flow. 7 …

Driver Modeling for Detection and Assessment of Driver Distraction: Examples from the UTDrive Test Bed
JHL Hansen, C Busso, Y Zheng… – IEEE Signal …, 2017 – ieeexplore.ieee.org
… Processing on the Move” [2], considered a range of topics for smart vehicles advance- ments that included driver behavior modeling using on-road driving data [3], driver status monitoring systems [4], smart driver monitoring [5], conversational in-vehicle dialog systems [6], active …

Systemic functional linguistics and computation: New directions, new challenges
J Bateman, D McDonald, T Hiippala… – … Handbook of Systemic …, 2017 – helsinki.fi
… include both the development of software tools (for information/document retrieval, document sum- marization, sentiment analysis, named entity … This included both Terry Winograd’s SHRDLU (Winograd 1972), a land- mark natural language dialogue system that demonstrated …

Active learning from peers
K Murugesan, J Carbonell – Advances in Neural Information …, 2017 – papers.nips.cc
… financial trading, email prioritization and filtering, personalized news, crowd source-based annotation, spam filtering and spoken dialog system, etc … Sentiment Analysis5 We evaluated our algorithm on product reviews from Amazon on a dataset containing reviews from 24 …

Sarcasm detection in microblogs using Naïve Bayes and fuzzy clustering
S Mukherjee, PK Bala – Technology in Society, 2017 – Elsevier
… Despite the difficulties, the huge benefit of detecting sarcasm has been recognized in many computer interaction based applications, such as, review summarization, dialogue systems and review … Maynard and Greenwood, 2014, Impact of sarcasm on sentiment analysis [16] …

Semantic specialisation of distributional word vector spaces using monolingual and cross-lingual constraints
N Mrkši?, I Vuli?, DÓ Séaghdha, I Leviant… – arXiv preprint arXiv …, 2017 – arxiv.org
… To the best of our knowledge, this is the first work on multilingual training of any compo- nent of a statistical dialogue system … parsing (Socher et al., 2013a; Bansal et al., 2014; Chen and Manning, 2014; Johannsen et al., 2015; Ammar et al., 2016), sentiment analysis (Socher et …

Semantic Comprehension System for F-2 Emotional Robot
A Kotov, N Arinkin, A Filatov, L Zaidelman… – First International Early …, 2017 – Springer
… researchers often use the bag-of-n-grams – an unordered set of tuples consisting of n consecutive words [2, 6]. Dialogue systems also often … T-expressions are used as the basis both for sentiment analysis task and for other applications such as automatic question answering …

Deep Survey on Sentiment Analysis and Opinion Mining on Social Networking Sites and E-Commerce Website
P Arya, A mit Bhagat, B MANIT – International Journal of Engineering …, 2017 – ijesc.org
… [32] developed emotionally sensitive spoken conversational interfaces combined an Emotion Recognition and a Sentiment Analysis methodologies … Authors also evaluated the proposed framework with the UAH (Universidad Al Habla) spoken dialog system, implementing the …

Emotion Recognition by Combining Prosody and Sentiment Analysis for Expressing Reactive Emotion by Humanoid Robot
Y Li, CT Ishi, N Ward, K Inoue… – … of APSIPA Annual …, 2017 – sap.ist.i.kyoto-u.ac.jp
… Backchannel generation has been applied in some dialog systems, producing effective attentive listening behavior [8, 9]. However, it is not … In this work, we aim at improving the emotion recognition, specifically valence, by combining prosody and sentiment analysis to make the …

The importance of multimodality in sarcasm detection for sentiment analysis
MS Razali, AA Halin, NM Norowi… – … (SCOReD), 2017 IEEE …, 2017 – ieeexplore.ieee.org
… D. Traum, and S. Narayanan, “’Yeah right’: sarcasm recognition for spoken dialogue systems.”, INTERSPEECH, p. 4, 2006. [5] D. Maynard and MA Greenwood, “Who cares about Sarcastic Tweets? Investigating the Impact of Sarcasm on Sentiment Analysis.,” LREC, pp …

Contextualizing Customer Complaints by Identifying Latent Beliefs and Tailoring a Chatbot’s Dialog through Epistemic Reasoning
C Anantaram, A Sangroya – mrc.kriwi.de
… ‘Lexi- con-based methods for sentiment analysis’, 2011. [Uckelman et al., 2010] U. Sara, “Obligationes as formal dialogue systems,” in Stairs 2010: Proceedings of the Fifth Starting AI Researchers’ Symposium, vol. 222. IOS Press, 2010, p. 341 …

Spoken dialogue BIM systems–an application of big data in construction
I Motawa – Facilities, 2017 – emeraldinsight.com
… Spoken dialogue systems System modules Case study Conclusions References Corresponding Author Previous section Next section … The sentiment analysis which is a form of textual analysis of social media can be then used to process these knowledge …

Statistical Language and Speech Processing: 5th International Conference, SLSP 2017, Le Mans, France, October 23–25, 2017, Proceedings
N Camelin, Y Estève, C Martín-Vide – 2017 – books.google.com
… analysis Parsing Part-of-speech tagging Question-answering systems Semantic role labeling Speaker identification and verification Speech and language generation Speech recognition Speech synthesis Speech transcription Spelling correction Spoken dialogue systems Term …

A “small-data”-driven approach to dialogue systems for natural language human computer interaction
T Boros, SD Dumitrescu – Speech Technology and Human …, 2017 – ieeexplore.ieee.org
… [5] JD Williams and S. Young, “Partially observable markov decision processes for spoken dialog systems,” Computer Speech & Language, vol … [9] CN Dos Santos and M. Gatti, “Deep convolutional neural networks for sentiment analysis of short texts.” in COLING, 2014, pp …

Opinion Mining in Twitter: How to make use of Sarcasm to Enhance Sentiment Analysis: A
S Parveen, A Surnar, S Sonawane – ijarcet.org
… Association for Computational Linguistics [4] Joseph Tepperman, DR “Yeah right: sarcasm recognition for spoken dialogue systems”, In Proceedings of INTERSPEECH [5] CC Liebrecht, FK “The perfect … “Gated neural networks for targeted sentiment analysis”, isnthirtieth sAAAI …

Tag Me a Label with Multi-arm: Active Learning for Telugu Sentiment Analysis
SS Mukku, SR Oota, R Mamidi – … Conference on Big Data Analytics and …, 2017 – Springer
… section, we give an overview of related work which is focused on: (i) Analysis of resource poor languages and their labeling techniques, (ii) Active learning and different query selection strategies, (iii) Sentiment analysis for regional … [13] developed a dialogue system for Telugu, a …

Improvised Comedy as a Turing Test
KW Mathewson, P Mirowski – arXiv preprint arXiv:1711.08819, 2017 – arxiv.org
… trained on cleaned and filtered subtitles from about 100k filmsA. Dialogue turn-taking, candidate sentence selection, and sentiment analysis [8] on … 6 to 70 years, with a median around 30, and a balanced gender distribution) was convinced that the dialog system understood the …

End-to-End Dialogue with Sentiment Analysis Features
A Rinaldi, O Oseguera, J Tuazon, AC Cruz – International Conference on …, 2017 – Springer
… its humanitarian applications. Keywords. Sequence-to-sequence learning Dialogue system Conversational agent Chatbot Recurrent neural network Sentiment analysis. Download fulltext PDF. 1 Introduction. Psychiatric care and …

Distinguishing between facts and opinions for sentiment analysis: Survey and challenges
I Chaturvedi, E Cambria, RE Welsch, F Herrera – Information Fusion, 2017 – Elsevier
… Sentiment analysis has raised growing interest both within the scientific community, leading to many exciting open challenges, as well as in … and political [30] forecasting, e-health [31] and e-tourism [32], human communication comprehension [33] and dialogue systems [34], etc …

Conclusion and Future Work
R Satapathy, E Cambria, A Hussain – Sentiment Analysis in the Bio …, 2017 – Springer
… This can be extended to multiple languages [7] for sentiment analysis in biomedical domain. Furthermore, a dialogue system as in [9], can be built for biomedical domain so as to keep patients calm by chatting with them. 5.1 Summary of Contributions …

In-the-wild chatbot corpus: from opinion analysis to interaction problem detection
I Maslowski, D Lagarde, C Clavel – pdfs.semanticscholar.org
… 83–95. [8] J. Liscombe, G. Riccardi, and D. Hakkani-Tür, “Using context to improve emotion detection in spoken dialog systems,” in Ninth European Conference on Speech Communication and Technology, 2005 … [17] C. Clavel and Z. Callejas, “Sentiment analysis: from opinion …

Natural Language Input for In-Car Spoken Dialog Systems: How Natural is Natural?
P Braunger, W Maier – Proceedings of the 18th Annual SIGdial Meeting …, 2017 – aclweb.org
… 2008. Towards human- like spoken dialog systems. Speech Communication 50:630–645. Ido Guy. 2016 … 2010. Twitter as a corpus for sentiment analysis and opinion mining. In Proceedings of the 7th International Conference on Language Resources and Evaluation (LREC) …

Chat-Bot For College Management System Using AI
K Bala, M Kumar, S Hulawale, S Pandita – 2017 – irjet.net
… KEYWORDS: NLP (Natural language processing), Sentiment Analysis, synsets, Word Net 1. INTRODUCTION … They differ mainly from the knowledge sources, the broadness of Dialog Systems (NLDS) is an appropriate and easy way to access information …

Eckhard Bick and Marcos Zampieri
J Koco?, M Marci?czuk, A Aghaebrahimian, F Jur?í?ek… – pdfs.semanticscholar.org
… 134 Natalia Loukachevitch and Aleksei Alekseev Short Messages Spam Filtering Using Sentiment Analysis … 470 Meysam Asgari, Allison Sliter, and Jan Van Santen Platon: Dialog Management and Rapid Prototyping for Multilingual Multi-user Dialog Systems …

A Chatbot for Psychiatric Counseling in Mental Healthcare Service Based on Emotional Dialogue Analysis and Sentence Generation
KJ Oh, D Lee, B Ko, HJ Choi – Mobile Data Management (MDM …, 2017 – ieeexplore.ieee.org
… [5] M. W?llmer, F. Weninger, T. Knaup, B. Schuller, C. Sun, K. Sagae, and LP Morency, “Youtube movie reviews: Sentiment analysis in an … M. Gasic, LM Rojas-Barahona, PH Su, and S. Young, “A network-based end-to-end trainable task- oriented dialogue system,” arXiv preprint …

Evaluation of Sentiment and Affectivity Analysis in a Blog Recommendation System
JPB Ferreira, FLA Junior, RL Rosa… – Proceedings of the XVI …, 2017 – dl.acm.org
… Author Keywords Recommendation system; social networks; sentiment analysis; Blogs; usability assessment; quality of experience … 2012. Sentiment Analysis: A tool for Rating Attribution to Content in Recommender Systems. In Proc …

Ethical Challenges in Data-Driven Dialogue Systems
P Henderson, K Sinha, N Angelard-Gontier… – arXiv preprint arXiv …, 2017 – arxiv.org
… Curry, AC; Hastie, H.; and Rieser, V. 2017. A review of evaluation techniques for social dialogue systems. arXiv preprint arXiv:1709.04409 … Hutto, CJ, and Gilbert, E. 2014. Vader: A parsimonious rule- based model for sentiment analysis of social media text …

Neural sentence embedding using only in-domain sentences for out-of-domain sentence detection in dialog systems
S Ryu, S Kim, J Choi, H Yu, GG Lee – Pattern Recognition Letters, 2017 – Elsevier
… Collecting ID sentences is a necessary step in building many data-driven dialog systems … We think that the task of OOD sentence detection is more similar to domain-category analysis than to other tasks such sentiment analysis or speech-act analysis, so we expect that the …

Tag Me a Label with Multi-arm: Active Learning for Telugu Sentiment Analysis
M Sandeep, SR Oota, R Mamidi – 2017 – web2py.iiit.ac.in
… section, we give an overview of related work which is focused on: (i) Analy- sis of resource poor languages and their labeling techniques, (ii) Active learning and different query selection strategies, (iii) Sentiment analysis for regional … [13] developed a dialogue system for Telugu …

Real Time Twitter Sentiment Analysis
S Singh, S Agarwal, S Agarwal – ijser.org
… showing irritation or to be funny. Recognition of sarcasm can ease many Sentiment Analysis NLP applications, such as review summarization, dialogue systems, review ranking systems, etc. This work was implemented on a …

Recognizing emotions in spoken dialogue with acoustic and lexical cues
L Tian, JD Moore, C Lai – Proceedings of the 1st ACM SIGCHI …, 2017 – dl.acm.org
… Therefore, it is desirable for virtual agent dialogue systems to recognize and react to user’s emotions … These features, inherited from speech processing and sentiment analysis, often overlook the context of the emotion recognition task which, in this case, is a spoken dialogue …

Application to Sentiment Analysis
R Satapathy, E Cambria, A Hussain – Sentiment Analysis in the Bio …, 2017 – Springer
… Application to Sentiment Analysis … The first class makes use of fully automatic creativity, eg, in computer games to develop plots or to compose music on the fly, or as a part of human-machine communication in dialogue systems and conversational agents …

Domain Complexity and Policy Learning in Task-oriented Dialogue Systems
A Papangelis, S Ultes, Y Stylianou – uni-ulm.de
… 3. Alexandros Papangelis and Yannis Stylianou, “Multi-domain spoken dialogue systems using domain-independent parameterisation,” in Domain … using domain similarity- and domain complexity-based in- stance selection for cross-domain sentiment analysis,” in 2012 IEEE …

Summarizing Dialogic Arguments from Social Media
A Misra, S Oraby, S Tandon, P Anand… – arXiv preprint arXiv …, 2017 – arxiv.org
Page 1. arXiv:1711.00092v1 [cs.CL] 31 Oct 2017 Summarizing Dialogic Arguments from Social Media Amita Misra, Shereen Oraby, Shubhangi Tandon, Sharath TS, Pranav Anand and Marilyn Walker UC Santa Cruz Natural Language and Dialogue Systems Lab 1156 N. High …

Combining speech-based and linguistic classifiers to recognize emotion in user spoken utterances
D Griol, JM Molina, Z Callejas – Neurocomputing, 2017 – Elsevier
… Although emotion is receiving increasing attention from the dialog systems community, most research described in the literature is … Our approach merges textual sentiment analysis and emotion recognition from paralinguistic features to respectively analyze the text transcription …

On the construction of more human-like chatbots: Affect and emotion analysis of movie dialogue data
RE Banchs – Asia-Pacific Signal and Information Processing …, 2017 – ieeexplore.ieee.org
… describe MovieDiC [11], the dataset used for the analysis conducted in this work, along with a chat-oriented dialogue system developed with … In their first application of Crystal Emotion in the context of sentiment analysis and sarcasm detection, Gupta and Yang [12] described the …

A Pilot Study on Using an Intelligent Life-like Robot as a Companion for Elderly Individuals with Dementia and Depression
H Abdollahi, A Mollahosseini, JT Lane… – arXiv preprint arXiv …, 2017 – arxiv.org
… Do the results of the pilot study show that each individual looked for different features (eg, spoken dialog system, cognitive games … Ryan uses the speech emotion recognition Aylien [24] system which is an online natural language processing service for sentiment analysis of the …

Markov reward models for analyzing group interaction
G Murray – Proceedings of the 19th ACM International Conference …, 2017 – dl.acm.org
… 2011. Lexicon-based Methods for Sentiment Analysis. Computational Linguistics 37, 2 (June 2011), 267?307 … 2007. Partially observable Markov decision processes for spoken dialog systems. Computer Speech & Language 21, 2 (2007), 393?422. [24] T. Wilson. 2008 …

Sarcasm Detection Using Sentiment Flow Shifts
E Filatova – 2017 – pdfs.semanticscholar.org
… Do we really need lexical information? towards a top-down approach to sentiment analysis of product reviews. In Proceedings of NAACL/HLT … “yeah right”: Sarcasm recognition for spoken dialogue systems. In Proceedings of INTERSPEECH, 1838–1841 …

ML-Ask: Open Source Affect Analysis Software for Textual Input in Japanese
M Ptaszynski, P Dybala… – Journal of …, 2017 – openresearchsoftware.metajnl.com
… affective states expressed by the user were also used as information on how the user feels about the dialog system they interact … indicate that such information, could be useful in determining distinguishable features for other tasks related to affect and sentiment analysis, or even …

Social Attractiveness in Dialogs
A Schweitzer, N Lewandowski, D Duran – Proc. Interspeech 2017, 2017 – researchgate.net
… for in- stance [4, 5, 6, 7, 8]). Other research on voice attractiveness, or pleasantness, is in the context of dialog systems aiming to … As an approximate sentiment analysis of the spoken words, we assigned positive and negative polarity to all tokens in the dialog transcripts using …

Introduction to Cyberemotions
JA Ho?yst – Cyberemotions, 2017 – Springer
… Although the next part, “Sentiment analysis” may look like quite disjoint from its predecessor, it is a key input for the following “Modelling … Outputs of the Project were used for creating new affective dialog systems as interactive tools as well as semi-automated simulation of facial …

UB at the NTCIR-13 STC-2 Task: Exploring Syntactic Similarities and Sentiments
J Wang – research.nii.ac.jp
… Keywords NTCIR-13, Short Text Conversation, Sentiment Analysis, Opinion Analysis, Re-Ranking … While much success has been achieved with task-oriented dialogue systems in constrained domains, there remain ma- jor problems with open domain dialogue systems, largely …

Sarcasm detection of tweets: A comparative study
T Jain, N Agrawal, G Goyal… – … Computing (IC3), 2017 …, 2017 – ieeexplore.ieee.org
… Sarcasm detection is one of the key challenges in sentiment analysis. In the past few years, with growing popularity of various Online Social Networks [16], Natural Language processing systems such as review summarization systems, dialogue systems and brand monitoring …

Sentiments Analysis of Reviews Based on ARCNN Model
X Xu, M Xu, J Xu, N Zheng, T Yang – IOP Conference Series …, 2017 – iopscience.iop.org
… [8] Liang and Y. Cai, Polarity Shifting and LSTM Based Recursive Networks for Sentiment Analysis [J]. Journal of Chinese … Building end-to-end dialogue systems using generative hierarchical neural network models[C]. Thirtieth AAAI Conference on Artificial Intelligence. 2016 …

Spanish Sign Language Recognition with Different Topology Hidden Markov Models
CD Mart?nez-Hinarejos… – Proc. Interspeech …, 2017 – pdfs.semanticscholar.org
… 1. Introduction Natural language technologies have been used in the last decades to provide solutions for many language related prob- lems, such as speech recognition [1], machine translation [2], dialogue systems [3], or sentiment analysis [4], among others …

Roving Mind: a balancing act between open–domain and engaging dialogue systems
A Cervone, G Tortoreto, S Mezza, E Gambi, G Riccardi – researchgate.net
… To the best of our knowledge RM represents the first attempt to build a modular, domain-independent dialogue system architecture, with an … The sentiment polarity qualifier records the attitude of a user towards the entities (or topics) present in FU, sentiment analysis is performed …

Conscious vs. Unaware Evaluation––Using Collective Intelligence for an Automatic Evaluation of Acts
R Rzepka, K Araki – researchgate.net
… Because it is not natural to ask an interlocutor (or the supervisor) for feedback every time a dialog system processes or generates an … 2.1 State of the Art Our research is a crossing of common sense knowledge ac- quisition, sentiment analysis and machine ethics, therefore it is …

Graph Enhanced Memory Networks for Sentiment Analysis
Z Xu, R Vial, K Kersting – Joint European Conference on Machine Learning …, 2017 – Springer
… ECML PKDD 2017: Machine Learning and Knowledge Discovery in Databases pp 374-389 | Cite as. Graph Enhanced Memory Networks for Sentiment Analysis … Typical examples include tree structure of a sentence and knowledge graph in a dialogue system …

Proceedings of the 29th Conference on Computational Linguistics and Speech Processing (ROCLING 2017)
LW Ku, Y Tsao – Proceedings of the 29th Conference on Computational …, 2017 – aclweb.org
… Technical Staff and Director of the Dialogue Systems Research Department. His research … 230 Multi-Channel Lexicon Integrated CNN-BiLSTM Models for Sentiment Analysis Joosung Yoon, Hyeoncheo Kim ….. 244 …

A Complete Bibliography of ACM Transactions on Speech and Language Processing (TSLP)
NHF Beebe – 2017 – tug.ctan.org
… Higashinaka:2004:EDU [HMNA04] Ryuichiro Higashinaka, Noboru Miyazaki, Mikio Nakano, and Kiyoaki Aikawa. Evaluating dis- course understanding in spoken dialogue systems. ACM Trans- actions on Speech and Language Processing (TSLP), 1(1):1–20, November 2004 …

Emotion Models: A Review
S PS, GS Mahalakshmi – researchgate.net
… bio-sensors: First steps towards an automatic system,” In Tutorial and Research Workshop on affective dialogue systems, pp … commonsense knowledge,” In Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis, Association for …

Text, Speech, and Dialogue: 20th International Conference, Tsd 2017, Prague, Czech Republic, August 27-31, 2017, Proceedings
K Ekštein, V Matoušek – 2017 – books.google.com
… One of the ambitions of the conference is, as its name suggests, not only to deal with dialogue systems but also to improve dialogue among researchers in areas of NLP, ie, among the … 66 Ahmad Aghaebrahimian Sentiment Analysis with Tree-Structured Gated Recurrent Units …

Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue
K Jokinen, M Stede, D DeVault, A Louis – Proceedings of the 18th …, 2017 – aclweb.org
… Frames: a corpus for adding memory to goal-oriented dialogue systems Layla El Asri, Hannes Schulz, Shikhar Sharma, Jeremie Zumer … Exploring Joint Neural Model for Sentence Level Discourse Parsing and Sentiment Analysis Bita Nejat, Giuseppe Carenini and Raymond Ng …

Non-Contextual Modeling of Sarcasm using a Neural Network Benchmark
V Ashokkumar, ND Radpour – 2017 – ttic.edu
… One of the most crucial components of natural human-robot interaction is artificial intuition and its influence on dialog systems … This is necessary for establishing a comprehensive sentiment analysis schema that is sensitive to the nuances of sarcasm- ridden text by being trained …

MojiTalk: Generating Emotional Responses at Scale
X Zhou, WY Wang – arXiv preprint arXiv:1711.04090, 2017 – arxiv.org
… and train an atten- tive bi-directional long-short term memory net- work (Hochreiter and Schmidhuber, 1997) model for sentiment analysis … use a reinforcement learning algorithm to improve the vanilla sequence-to-sequence model for non-task- oriented dialog systems, but their …

Predicting Users’ Negative Feedbacks in Multi-Turn Human-Computer Dialogues
X Wang, J Wang, Y Liu, X Wang, Z Wang… – Proceedings of the Eighth …, 2017 – aclweb.org
… User experience is essential for human- computer dialogue systems … Meanwhile, this problem cannot be cov- ered by classical sentiment analysis task because users’ sentiment intention tends to be not obvious, and more importantly, the facts causing negative feedbacks are …

Proceedings of the 2nd Workshop on Representation Learning for NLP
P Blunsom, A Bordes, K Cho, S Cohen, C Dyer… – Proceedings of the 2nd …, 2017 – aclweb.org
… Gradual Learning of Matrix-Space Models of Language for Sentiment Analysis Shima Asaadi and Sebastian Rudolph … A Frame Tracking Model for Memory-Enhanced Dialogue Systems Hannes Schulz, Jeremie Zumer, Layla El Asri and Shikhar Sharma …

6 Computational Analysis of Vocal Expression of Affect: Trends and Challenges
K Scherer, B Schüller, A Elkins – Social Signal Processing, 2017 – books.google.com
… Using context to improve emotion detection in spoken dialog systems. In Proceedings of INTERSPEECH (pp. 1845–1848) … Brisbane, Australia: ISCA. Wöllmer, M., Weninger, F., Knaup, T., et al.(2013). YouTube movie reviews: Sentiment analysis in an audiovisuall context …

Intension classification of user queries in intelligent customer service system
S Song, H Chen, Z Shi – Asian Language Processing (IALP) …, 2017 – ieeexplore.ieee.org
… have been shown to boost the performance in multiple NLP tasks such as machine translation and sentiment analysis, by representing per … classification in QA system can also be taken as Dialogue Intention Recognition (DIR) [5], and in dialogue systems, understanding user …

Designing Humour in Human Computer Interaction (HUMIC 2017)
A Niculescu, A Valitutti, R Banchs – 16th IFIP Conference on Human …, 2017 – hal.inria.fr
… Infocomm Research in Singapore. His recent areas of research include Machine Translation, Information Retrieval, Cross-language Information Retrieval, Sentiment Analysis and Dialogue Systems. More specifically, he has …

Sarcasm detection of non# tagged statements using MLP-BP
P Gidhe, L Ragha – Advances in Computing, Communication …, 2017 – ieeexplore.ieee.org
… Opinion mining or sentiment analysis is the field where research has been carried out since last decades … may contain an implied positive or negative sentiment[1]. Natural language processing(NLP) systems such as online review sum- marization, dialog system, chatbot etc …

QUICK RECAPITULATION WHAT HAVE WE LEARNED?
WHWE LEARNED – idt.mdh.se
… software engineering, statistics, machine learning • Different applications: machine translation, dialogue systems, natural language … Text: morphology, syntax, semantics, annotation, information retrieval, summarisation, sentiment analysis, generation, translation, captioning …

Improvement sarcasm analysis using NLP and corpus based approach
MY Manohar, P Kulkarni – Intelligent Computing and Control …, 2017 – ieeexplore.ieee.org
… [4] D. Maynard and MA Greenwood, “Who cares about sarcastic tweets? Investigating the impact of sarcasm on sentiment analysis,” in Proc … 2012. [15] J. Tepperman, D. Traum, and SS Narayanan, “`Yeah right’: Sarcasm recognition for spoken dialogue systems,” in Proc …

Synthesising uncertainty: the interplay of vocal effort and hesitation disfluencies
E Székely, J Mendelson, J Gustafson – 18th Annual Conference of …, 2017 – isca-speech.org
… At the same time, it provides insight into what extent spoken dialogue systems using a syn- thetic voice would be capable of … Sentiment analysis was performed with the Stanford Deep Learning for Sentiment Analysis parser [34] to select neutral sentences in order to avoid further …

An Ensemble Model with Ranking for Social Dialogue
I Papaioannou, AC Curry, JL Part, I Shalyminov… – arXiv preprint arXiv …, 2017 – arxiv.org
… This paper discusses two of the major challenges when building open-domain social dialogue systems: 1. How can we facilitate open domain interaction while still executing control … VADER: A parsimonious rule-based model for sentiment analysis of social media text …

A Semi-Supervised Approach to Detecting Stance in Tweets
A Misra, B Ecker, T Handleman, N Hahn… – arXiv preprint arXiv …, 2017 – arxiv.org
… Amita Misra, Brian Ecker, Theodore Handleman, Nicolas Hahn and Marilyn Walker Natural Language and Dialogue Systems Lab University of California, Santa Cruz 1156 N. High … 1 https://www.cs.uic.edu/ liub/FBS /sentiment-analysis.html 2 http://neuro.imm.dtu.dk/wiki/AFINN …

ICDMW 2017
B Bhattacharya, I Burhanuddin, A Sancheti, K Satya – ieeexplore.ieee.org
… A Politically-Sensitive Dialog System Based on Twitter Data …..393 Aparup Khatua, Erik Cambria … Phonetic-Based Microtext Normalization for Twitter Sentiment Analysis …..407 Ranjan Satapathy, Claudia Guerreiro, Iti …

Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
G Kondrak, T Watanabe – Proceedings of the Eighth International Joint …, 2017 – aclweb.org
… 506 xvii Page 18. Implicit Syntactic Features for Target-dependent Sentiment Analysis Yuze Gao, Yue Zhang and Tong Xiao … 723 End-to-End Task-Completion Neural Dialogue Systems Xiujun Li, Yun-Nung Chen, Lihong Li, Jianfeng Gao and Asli Celikyilmaz …

Sarcasm Identification on Twitter: A Machine Learning Approach
A Onan – Computer Science On-line Conference, 2017 – Springer
… Decis. Support Syst. 57, 77–93 (2014)CrossRefGoogle Scholar. 2. Fersini, E., Messina, E., Pozzi, FA: Sentiment analysis: Bayesian ensemble learning. Decis … Tepperman, J., Traum, DR, Narayanan, S.: “yeah right”: sarcasm recognition for spoken dialogue systems …

Breaking the internet barrier
M Li, X Zhu – 2017 – idl-bnc-idrc.dspacedirect.org
… 3. Hao Zhou, Minlie Huang, Xiaoyan Zhu. Context-aware Natural Language Generation for Spoken Dialogue Systems. COLING 2016, Osaka, Japan … Minlie Huang, Borui Ye, Yichen Wang, Xiaoyan Zhu. New Word Detection for Sentiment Analysis. ACL 2014, June 23-25, 2014 …

Design and Evaluation Methods, Tools and Practices
K Angkananon, M Wald, P Ploadaksorn, TP Anjos… – pdfs.semanticscholar.org
… 450 Junko Itou, Rina Tanaka, and Jun Munemori Collection of Example Sentences for Non-task-Oriented Dialog Using a Spoken Dialog System and Comparison with Hand-Crafted DB … XX Contents – Part I Page 7. End-to-End Dialogue with Sentiment Analysis Features …

Building CMU Magnus from User Feedback
S Prabhumoye, F Botros, K Chandu… – Alexa Prize …, 2017 – nzini.com
… improved. 6 Conclusion It is hard to build a spoken dialog system without conversations from real users. With … 2012. [5] CJ Hutto and E. Gilbert. Vader: A parsimonious rule-based model for sentiment analysis of social media text. In …

Li18 Computational Linguistics December 2017
N Ballou – 2017 – nickballou.com
… Spanish, Swedish, Ukrainian, Urdu Page 3. 3. Information retrieval 4. Document classification 5. Question answering 6. Sentiment analysis 7. Learner text assessment 8. Machine translation 9. Dialogue systems Given this sketch of …

Emojive! Collecting Emotion Data from Speech and Facial Expression using Mobile Game App
JH Park, N Lee, D Bertero, A Dey, P Fung – Proc. Interspeech 2017, 2017 – isca-speech.org
… Most challenging problem of training modules for tasks like emotion recognition and sentiment analysis is that each requires huge amounts of data, since it … [1] D. Bertero et al, “Real-Time Speech Emotion and Sentiment Recognition for Interactive Dialogue Systems”, 2016 [2] J …

Statistical Language and Speech Processing
N Camelin, Y Estève, C Martín-Vide – Springer
… analysis Parsing Part-of-speech tagging Question-answering systems Semantic role labeling Speaker identification and verification Speech and language generation Speech recognition Speech synthesis Speech transcription Spelling correction Spoken dialogue systems Term …

Emotion Detection from Text via Ensemble Classification Using Word Embeddings
J Herzig, M Shmueli-Scheuer… – Proceedings of the ACM …, 2017 – dl.acm.org
… input to neural net- works to improve sentiment analysis classi cation [14, 27]. This approach also requires large-scale data for the neural network training. Forgues [10] used pre-trained word vectors and a linear classi er to classify user intents in dialog systems, however their …

An Efficient Approach for Sarcasm Recognition on Twitterusing Pattern-Based Method
K ShehlaKulsum, SG Vaidya – ijarcet.org
… Detection of sarcasm is important for the enhancement of sentiment analysis systems[6] [7]. Apart from this, failure to detect sarcasm can cause problems in some Natural … dialogue systems, opinion oriented summarization[16], etc.because of inability to detect sarcastic comments …

Geometries of Word Embeddings
P Viswanath – pdfs.semanticscholar.org
… 21 Different datasets: pairs of sentences • algorithm rates similarity • compare to human scores • Average improvement of 4% Page 20. Sentiment Analysis Postprocessing in downstream applications This movie was funny and witty Classifier Page 21. Recurrent neural networks …

Recognizing the sarcastic statement on WhatsApp Group with Indonesian language text
E Winarko, A Cherid – Broadband Communication, Wireless …, 2017 – ieeexplore.ieee.org
… for sarcastic statements may create difficulties for many Natural Language Processing (NLP) based system such as online review summarization systems, dialogue systems or brand monitoring systems due to the failure of state of the art sentiment analysis systems to detect …

A Study on Sarcasm Detection Algorithms
L Sivaprakasam, A Jayaprakash – 2017 – pdfs.semanticscholar.org
… CHALLENGES FACED Natural Language Processing systems such as Online customer review summarization systems, dialogue systems or monitoring systems … fact denotes that the detection of sarcastic sentences lead to the improvement of sentiment analysis, namely positive …

Turn-taking Estimation Model Based on Joint Embedding of Lexical and Prosodic Contents
C Liu, C Ishi, H Ishiguro – Proc. Interspeech 2017, 2017 – pdfs.semanticscholar.org
… Furthermore, recog- nizing whether a phrase is backchannel is critical for a dialog system since it means a user has no intention to interrupt and requires no response; the system should … 23] used it with an LSTM layer and reported an improved result in a sentiment analysis task …

An Affect-Aware Dialogue System for Counseling
L Ring – 2017 – search.proquest.com
An Affect-Aware Dialogue System for Counseling. Abstract … interactive web pages for the user to read [106] , or by mimicking face-to-face conversations. through the use of complex dialogue systems built upon models of human discourse [4] . While …

Intelligent Personal Assistant with Knowledge Navigation
A Kumar, R Dutta, H Rai – arXiv preprint arXiv:1704.08950, 2017 – arxiv.org
… Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2, 1–135 … Rieser, V., & Lemon, O. (2013). Reinforcement learning for adaptive dialogue systems: A data-driven methodology for dialogue management and natural language generation …

An Overview of Open-Source Chatbots Social Skills
A Augello, M Gentile, F Dignum – International Conference on Internet …, 2017 – Springer
… This is a logical starting point for dialogue systems as the topic of a conversation is also part of the linguistic context … In: WISDOM Workshop at KDD (2015)Google Scholar. 16. Clavel, C., Callejas, Z.: Sentiment analysis: from opinion mining to human-agent interaction …

The commercial NLP landscape in 2017
R Dale – Natural Language Engineering, 2017 – cambridge.org
… these chatbots are conceptually similar to the much older category of telephony-based spoken language dialogue systems that let … provided by every vendor in the space, are named entity recognition, concept extraction, text classification, sentiment analysis, summarisation, and …

Subjective Text Mining for Arabic Social Media
NFB Hathlian, AM Hafez – … Journal on Semantic Web and Information …, 2017 – igi-global.com
… 12 Haaff, M. d. (2010). Sentiment Analysis, Hard But Worth It! Customer- Think … Hijjawi, M., & Bander, Z. (2011). An Arabic Stemming Approach using Machine Learning with Arabic Dialogue System. Proceedings of the ICGST AIML ’11Conference. Dubai: UAE …

Non-Contextual Modeling of Sarcasm using a Neural Network Benchmark
ND Radpour, V Ashokkumar – arXiv preprint arXiv:1711.07404, 2017 – arxiv.org
… Abstract One of the most crucial components of natural human-robot interaction is artificial intuition and its influence on dialog systems … This is necessary for establishing a comprehensive sentiment analysis schema that is sensitive to the nuances of sarcasm-ridden text by …

SENTIMENT ANALYSIS IN CZECH
K Veselovská – 2017 – ufal.mff.cuni.cz
… applicable not only in sentiment analysis (as described in detail in Chap- ter 9), but also in many other areas of natural language processing, such as question- answering, recommendation systems, automatic summarization of a text, automatic dialogue systems or emotionality …

Chatbot as an Intermediary between a Customer and the Customer Care Ecosystem
A Sangroya, P Saini, C Anantaram – Proceedings of the 9th International …, 2017 – dl.acm.org
… [12] Sara, U. Obligationes as formal dialogue systems. In Proceedings of the Fifth Starting AI Researchers’ Symposium (2010). [13] Taboada, M., Tofiloski, M., Brooke, J., Voll, K., and Stede, M. Lexicon-based methods for sentiment analysis, 2011 …

” Having 2 hours to write a paper is fun!”: Detecting Sarcasm in Numerical Portions of Text
L Kumar, A Somani, P Bhattacharyya – arXiv preprint arXiv:1709.01950, 2017 – arxiv.org
… This shows that special attention to text containing numbers may be useful to im- prove state-of-the-art in sarcasm detection. 1 Introduction Computational detection of sarcasm has seen at- tention from the sentiment analysis community in the past few years (Joshi et al., 2016a) …

Robust Task Clustering for Deep and Diverse Multi-Task and Few-Shot Learning
M Yu, X Guo, J Yi, S Chang, S Potdar, G Tesauro… – 2017 – openreview.net
… 2. Diverse Real-World Tasks: User Intent Classification for Dialog System The second dataset is from an on-line service which trains and serves intent classification models to various clients … 5In conversational dialog systems, intent-labels are used to guide the dialog-flow. 7 …

An Agent-Based Aggression De-escalation Training Application for Football Referees
T Bosse, W van Breda, N van Dijk, J Scholte – Portuguese Conference on …, 2017 – Springer
… players. The prototype combines three elements, namely a dialogue system, a computational model of Leary’s Rose, and a module for sentiment analysis. All this is implemented within an application that runs on Android devices …

Feature-based Compositing Memory Networks for Aspect-based Sentiment Classification in Social Internet of Things
R Ma, K Wang, T Qiu, AK Sangaiah, D Lin… – Future Generation …, 2017 – Elsevier
… 2014. Abstract. Sentiment analysis is an important research field in natural language processing … sentence. Keywords. Sentiment analysis. Memory networks. Aspect-based Sentiment Classification. Attention mechanism. 1. Introduction …

Emotional Human-Machine Conversation Generation Based on Long Short-Term Memory
X Sun, X Peng, S Ding – Cognitive Computation, 2017 – Springer
… Several attempts have been made to endow dialog systems or conversational agents with emotion [2, 33]. Kadish et al … [37] proposed a natural language dialog system that can estimate the user’s emotion from utterances and respond on the basis of the estimated emotion …

Detecting and Adapting Conversational Agent Strategy to User’s Emotions in Video Games
B Cagnol – 2017 – macs.hw.ac.uk
… 3 1.1.1.1 Current Dialogue System . . . . . 3 1.1.1.2 Natural Language Generation and Open Dialogue … 7 1.2 Detecting and adapting to user’s emotions . . . . . 7 1.2.1 Sentiment Analysis …

Multi-level mining and visualization of scientific text collections: Exploring a bi-lingual scientific repository
P Accuosto, F Ronzano, D Ferrés… – Proceedings of the 6th …, 2017 – dl.acm.org
… relation sentiment analysis emotion polarity text emotions sentiment classi cation emotional level negative positive annotation … words dialogue systems user dialogue system information models model items speech goals interaction web …

Computational Study of Primitive Emotional Contagion in Dyadic Interactions
G Varni, I Hupont, C Clavel… – IEEE Transactions on …, 2017 – ieeexplore.ieee.org
… Index Terms—Primitive emotional contagion, facial expressions analysis, sentiment analysis, cross-recurrence quantification analysis. ? 1 INTRODUCTION … TABLE 1: Validation: contingency table of the utterances’ polarity detected by the sentiment analysis algorithm. No …

AppTechMiner: Mining Applications and Techniques from Scientific Articles
M Singh, S Dan, S Agarwal, P Goyal… – Proceedings of the 6th …, 2017 – dl.acm.org
… Word Alignment, Conditional Random Fields, Maximum Entropy, Coreference Resolution, Machine Learning, Dialogue Systems, Textual Entailment, Natural Language Understanding, Active Learning, POS Tagging, Relation Extraction, Sentiment Analysis, Sense Induction …

THIN FILM ROUGHNESS OPTIMIZATION IN THE TIN COATINGS USING GENETIC ALGORITHMS
NURF FAUZI, ASM JAYA, MI JARRAH, H AKBAR… – Journal of Theoretical …, 2017 – jatit.org
… 2017 — Vol. 95. No. 24 — 2017. Full Text. Title: ONLINE PERFORMANCE DIALOGUE SYSTEM MODEL (e-DP): A REQUIREMENT ANALYSIS STUDY AT BATU PAHAT DISTRICT EDUCATION OFFICE. Author: ASRAR NAJIB …

From Shakespeare to Twitter: What are Language Styles all about?
W Xu – Proceedings of the Workshop on Stylistic Variation, 2017 – aclweb.org
… user demo- graphic factors also shows benefits on improving natural language processing applications such as sentiment analysis (Volkova et al … Another subsequent challenge is how to transfer the subtle style differences into natural language generation and dialog systems …

Active learning in annotating micro-blogs dealing with e-reputation
JV Cossu, A Molina-Villegas… – arXiv preprint arXiv …, 2017 – arxiv.org
… crucial information. Mots-Clés Opinion Mining, Online Reputation Monitoring, Active Learning, Machine Learning, Human An- notation, Methodology, Sentiment Analysis, Topic Categorization, Natural Language Processing I …

Understanding sarcasm in speech using mel-frequency cepstral coefficent
A Mathur, V Saxena, SK Singh – Cloud Computing, Data …, 2017 – ieeexplore.ieee.org
… The work done for sentiment analysis follows the following procedure, firstly we n eed to pro cess the input file and check if the format of the input file is supported by FFMPEG … sa rcasm recognition for sp oken Dialogue systems”, Proceedings of Interspeech, pp.1838Y1841, 2006 …

Natural Language Processing: State of The Art, Current Trends and Challenges
D Khurana, A Koli, K Khatter, S Singh – arXiv preprint arXiv:1708.05148, 2017 – arxiv.org
… Emotion Detection (Shashank Sharma, 2016) [34] is similar to sentiment analysis, but it works on social media platforms on mixing of two languages (English + Any other Indian Language). It categorizes statements into six groups based on emotions … 6.6 Dialogue System …

General Pipeline Architecture for Domain-Specific Dialogue Extraction from different IRC Channels
A Abouzeid – 2017 – content.grin.com
… 19 machine using voice commands or in Dialogue Systems. (5) Computational Biology when comparing two strings representing humans DNA. (6) Information Retrieval [24]. (7) Information Extraction [27]. (8) Sentiment Analysis [20] …

Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
M Lapata, P Blunsom, A Koller – Proceedings of the 15th Conference of …, 2017 – aclweb.org
… this talk, I will take a fresh look at this question, drawing on simulations with pseudowords, sentiment analysis experiments, psycholinguistics … A Network-based End-to-End Trainable Task-oriented Dialogue System Tsung-Hsien Wen, David Vandyke, Nikola Mrkšic, Milica Gasic …

How Online Emotions Influence Community Life
J Sienkiewicz, A Chmiel, P Sobkowicz, JA Ho?yst – Cyberemotions, 2017 – Springer
… 9.3.2 User Emotions. As mentioned in the Introduction, the recent progress in automatic sentiment analysis gives the ability to quantify the emotional content of large scale textual data. This has already led to observations of emotionally-linked communities in blogs (Mitrovi? et al …

Discovering the Recent Research in Natural Language Processing Field Based on a Statistical Approach
X Chen, B Chen, C Zhang, T Hao – International Symposium on Emerging …, 2017 – Springer
… synthesis. Gradually, researchers also focus on the applications of relevant tools in solving real-world problems, eg, spoken dialogue systems, speech-to-speech translation engines, as well as sentiment analysis. NLP technologies …

Towards Debate Automation: a Recurrent Model for Predicting Debate Winners
P Potash, A Rumshisky – Proceedings of the 2017 Conference on …, 2017 – aclweb.org
Page 1. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 2465–2475 Copenhagen, Denmark, September 7–11, 2017. cO2017 Association for Computational Linguistics Towards …

Multi-level mining and visualization of scientific text collections
P Accuosto, F Ronzano, D Ferrés, H Saggion – 2017 – repositori.upf.edu
… relation sentiment analysis emotion polarity text emotions sentiment classification emotional level negative positive annotation … words dialogue systems user dialogue system information models model items speech goals interaction web …

On the Identification of Suggestion Intents from Vietnamese Conversational Texts
TL Ngo, KL Pham, H Takeda, SB Pham… – Proceedings of the Eighth …, 2017 – dl.acm.org
… role”. We can understand that a turn is a talking section in spoken dialog systems, a post/comment in forums, a twice/status in social media networks. (3 … Liu. 2016. Sentiment Analysis in Social Networks. Morgan Kaufmann. [19 …

Sequence Modeling with Hierarchical Deep Generative Models with Dual Memory
Y Zheng, L Wen, J Wang, J Yan, L Ji – Proceedings of the 2017 ACM on …, 2017 – dl.acm.org
… Extended experiments including document modeling and sentiment analysis, prove the high-effectiveness of dual memory mechanism and latent … tasks towards multiple applications related to language understanding, such as machine translation [2, 7], dialogue system [35, 36 …

Natural Logic Inference for Emotion Detection
H Ren, Y Ren, X Li, W Feng, M Liu – Chinese Computational Linguistics …, 2017 – Springer
… in natural language processing, emotion detection is widely used in opinion mining, product recommendation, dialog system, and so on … In: Proceedings of The 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis, Portland, Oregon (2011) …

An Adaptive Learning with Gamification & Conversational UIs: The Rise of CiboPoliBot
A Fadhil, A Villafiorita – Adjunct Publication of the 25th Conference on …, 2017 – dl.acm.org
… A work by Mazur et. al., [7] proposed a free talking dialogue system designed for tutoring English language … Therefore, chatbots are a great candidates to perform sentiment analysis and extract emotional context from a text corpus. A work by Lin et …

Neural Text Generation: A Practical Guide
Z Xie – arXiv preprint arXiv:1711.09534, 2017 – arxiv.org
… target. The lack of such a correspondence leads to issues in decoding which we focus on in Section 5. The same reasoning applies to sequence classification tasks such as sentiment analysis. 2.2 Encoder-decoder models Encoder …

QUESTION ANSWERING SYSTEM: A REVIEW ON QUESTION ANALYSIS, DOCUMENT PROCESSING, AND ANSWER EXTRACTION TECHNIQUES.
FS UTOMO, N SURYANA… – Journal of Theoretical & …, 2017 – search.ebscohost.com
Page 1. Journal of Theoretical and Applied Information Technology 31st July 2017. Vol.95. No 14 © 2005 – ongoing JATIT & LLS ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195 3158 QUESTION ANSWERING SYSTEM : A REVIEW ON …

Alibaba Group–Intelligent Innovation Division
H Chen – pdfs.semanticscholar.org
… 1. Answer rendering 2. Logging Computation 1. Similarity 2. Sentiment analysis 3. Attribute identification Indexing … References Wen TH, Vandyke D, Mrksic N, et al. A Network-based End-to-End Trainable Task-oriented Dialogue System[J]. 2016. task generation …

Find the Conversation Killers: a Predictive Study of Thread-ending Posts
Y Jiao, C Li, F Wu, Q Mei – arXiv preprint arXiv:1712.08636, 2017 – arxiv.org
Page 1. Find The Conversation Killers: A Predictive Study of Thread-ending Posts Yunhao Jiao Zhejiang University jiao_yunhao@zju.edu.cn Cheng Li University of Michigan lichengz@umich.edu Fei Wu Zhejiang University wufei@zju.edu.cn …

Practical data science for the web professional
M Nescot – Journal of Digital & Social Media Marketing, 2017 – ingentaconnect.com
… Using techniques such as natural language processing, sentiment analysis and … Dialogue systems Such applications include not only general purpose conversational agents and bots that resemble or compete with Alexa or Siri, but also specific extensions to such existing …

Knowledge-driven Support for Reminiscence on Companion Robots
L Asprino, A Gangemi, AG Nuzzolese, V Presutti… – pdfs.semanticscholar.org
… present a prototypical implementation of a dialogue system for reminiscing about images [8]. The system builds on a KB for storing … to acquire factual knowledge from the conversational interaction with the user, as well as the introduction of sentiment analysis capabilities to …

Evaluation of Modern Tools for an OMSCS Advisor Chatbot
E Gregori – 2017 – smartech.gatech.edu
… retention. Sentiment analysis can be used to classify customer satisfaction … Watson. “?A text based natural language dialogue system specifically developed for the purpose of holding structured, goal directed coaching conversations …

A Robot Commenting Texts in an Emotional Way
L Volkova, A Kotov, E Klyshinsky, N Arinkin – Conference on Creativity in …, 2017 – Springer
… (eds.): Affective Dialogue Systems. Springer, Berlin (2004)Google Scholar. 3. Bell, L., Gustafson, J., Heldner, M.: Prosodic adaptation in human–computer interaction … Kotov, A., Zinina, A., Filatov, A.: Semantic parser for sentiment analysis and the emotional computer agents …

Affect in the ICT context
P Zhang, JLS Yan – The Routledge Companion to Management …, 2017 – taylorfrancis.com
… Textual signals Automatic emotion detection in text falls in the general area of sentiment analysis (Pang & Lee, 2008) and is concerned with the use of computational models to identify segments of written text expressing emotions …

Detecting sarcasm in customer tweets: an NLP based approach
S Mukherjee, PK Bala – Industrial Management & Data Systems, 2017 – emeraldinsight.com
… from the implicit one, cannot be effectively identified with conventional data mining techniques such as sentiment analysis (Yee Liau … sarcasm has been recognized in many computer interaction-based applications, such as review summarization, dialogue systems and review …

Toward controlled generation of text
Z Hu, Z Yang, X Liang… – International …, 2017 – proceedings.mlr.press
… we can en- code structured constraints (eg, logic rules or probabilistic structured models) on the interpretable latent code, to in- corporate prior knowledge or human intentions (Hu et al., 2016a;b); or plug the disentangled generation model into dialog systems to generate …

Snowbot: An empirical study of building chatbot using seq2seq model with different machine learning framework
P Guo, Y Xiang, Y Zhang, W Zhan – pdfs.semanticscholar.org
… on the domain and length of input, RNN + LSTM can be used for sequence classification, text generation, translation, dialog system etc. as shown in table 2 Table 2: Variants of RNN + LSTM Type Input Output Example seq2one (classification) sentence class Sentiment analysis …

Language Technologies for the Challenges of the Digital Age
G Rehm, T Declerck – Springer
… Wustmann A Comparative Study of Uncertainty Based Active Learning Strategies for General Purpose Twitter Sentiment Analysis with Deep … Strötgen A Case Study on the Relevance of the Competence Assumption for Implicature Calculation in Dialogue Systems …

Learning to predict the adequacy of answers in chat-oriented humanagent dialogs
LF D’Haro, RE Banchs – Region 10 Conference, TENCON …, 2017 – ieeexplore.ieee.org
… Sentiment analysis: Using the text library TextBlob2 we obtained a score for subjectivity (between 0.0 and 1.0) and polarity (between -1.0 and 1.0) of each turn … IRIS: a chat-oriented dialogue system based on the vector space model. ACL: System Demonstrations, pages 3742 …

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
R Barzilay, MY Kan – Proceedings of the 55th Annual Meeting of the …, 2017 – aclweb.org
… Mausam (Information Extraction and NLP Applications Area) Omri Abend (Multilingual Area) Eugene Agichtein (Information Extraction and NLP Applications Area) Ron Artstein (Dialogue and Interactive Systems Area) Alexandra Balahur (Sentiment Analysis and Opinion Mining …

Speech Emotion Recognition based on Gaussian Mixture Models and Deep Neural Networks
IJ Tashev, ZQ Wang, K Godin – Information Theory and …, 2017 – ieeexplore.ieee.org
… With better understanding of the human and the emotion in spoken query, the spoken dialog system can thus achieve a better … This makes it similar to speaker identification [1], gesture recognition, sentiment analysis in natural language processing [2], and other classification …

A Bridge from the Use-Mention Distinction to Natural Language Processing
S Wilson – The Semantics and Pragmatics of Quotation, 2017 – Springer
… This serves as motivation to develop dialogue systems that, when appropriate, are capable of responding to problems in dialogue using the same familiar strategies … Sentiment Analysis: Sentiments expressed in mentioned language are not always shared by the language user …

Approaches for Computational Sarcasm Detection: A Survey
L Kumar, A Somani, P Bhattacharyya – pdfs.semanticscholar.org
… Abstract Sentiment Analysis deals not only with the positive and negative sentiment detec- tion in the text but it also considers the prevalence and challenges of sarcasm in sentiment-bearing text. Automatic Sar- casm detection deals with the detection of sarcasm in text …

Knowledge Guided Short-Text Classification for Healthcare Applications
S Cao, B Qian, C Yin, X Li, J Wei… – Data Mining (ICDM) …, 2017 – ieeexplore.ieee.org
… 1 shows, the chatbot faces a big challenge to determine the user’s intent in a typical dialog system if the utterance contains unrecognized entity words … In a sentiment analysis task, the positive/negative vocabulary would guide the classifier to fastly attend the correct direction …

Sentence?Chain Based Seq2seq Model for Corpus Expansion
E Chung, JG Park – ETRI Journal, 2017 – Wiley Online Library
… As a lexicon-based approach, WordNet is an external resource that is almost always available. WordNet has been utilized as a query expansion technique [13] for information retrieval and feature selection for sentiment analysis [14] …

Word affect intensities
SM Mohammad – arXiv preprint arXiv:1704.08798, 2017 – arxiv.org
… ing: tracking brand and product perception, track- ing support for issues and policies, tracking pub- lic health and well-being, literary analysis, devel- oping more natural dialogue systems, and disas- ter … A new ANEW: Evaluation of a word list for sentiment analysis in microblogs …

Convolutional recurrent neural network for question answering
MMA Zaman, SZ Mishu – Electrical Information and …, 2017 – ieeexplore.ieee.org
… Processing (NLP) can be presented as a question answering problem [1]. Moreover, QA can be used to develop dialogue systems and chatbots [2 … Dos Santos and Gatti have achieved state of the art result in sentiment analysis of single sentence using CNN [11], CNN has also …

Not All Dialogues are Created Equal: Instance Weighting for Neural Conversational Models
P Lison, S Bibauw – arXiv preprint arXiv:1704.08966, 2017 – arxiv.org
… the form of factual information or entity-grounded opinions, which is a important requirement for developing task-oriented dialogue systems … A popular strategy for domain adaptation, which has notably been used for POS-tagging, sentiment analysis, spam filtering and machine …

Bringing Semantic Structures to User Intent Detection in Online Medical Queries
C Zhang, N Du, W Fan, Y Li, CT Lu, PS Yu – arXiv preprint arXiv …, 2017 – arxiv.org
Page 1. Bringing Semantic Structures to User Intent Detection in Online Medical Queries Chenwei Zhang?¶, Nan Du†, Wei Fan‡, Yaliang Li†, Chun-Ta Lu?, Philip S. Yu?§ ? Department of Computer Science, University of Illinois …

Emotion detection: a technology review
JM Garcia-Garcia, VMR Penichet… – Proceedings of the XVIII …, 2017 – dl.acm.org
… Although emotion detection from text (also referred as sentiment analysis) must face more obstacles than the previous technologies (spelling errors, languages, slang), it is another source of affective information to consider … 2017. Sentiment Analysis …

Towards a top-down policy engineering framework for attribute-based access control
M Narouei, H Khanpour, H Takabi, N Parde… – Proceedings of the …, 2017 – dl.acm.org
… 4.2 Recurrent Neural Network (RNN) Sentence Classi er Recently, DNNs have been used with increasing frequency in a variety of text processing applications, from sentiment analysis [41] to conversational text processing for dialogue systems [22, 48]. Collobert et al …

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
M Palmer, R Hwa, S Riedel – Proceedings of the 2017 Conference on …, 2017 – aclweb.org
… Srikumar, University of Utah Sentiment Analysis and Opinion Mining Bing Liu, University of Illinois at Chicago Rada Mihalcea, University of Michigan Saif M. Mohammad, National Research Council Canada Social Media and …

Identifying and avoiding confusion in dialogue with people with alzheimer’s disease
H Chinaei, LC Currie, A Danks, H Lin, T Mehta… – Computational …, 2017 – MIT Press
… interaction. Given that 33% of conversations with people with middle-stage AD involve a breakdown in communication, it is vital that automated dialogue systems be able to identify those breakdowns and, if possible, avoid them …

Geometry of Compositionality.
H Gong, S Bhat, P Viswanath – AAAI, 2017 – aaai.org
… Salehi, Cook, and Baldwin 2015). Detection of sarcasm and metaphor is of great impor- tance in language processing applications like text analy- sis, dialogue systems and sentiment analysis. Recent works have used extensive …

An Empirical Study on Incorporating Prior Knowledge into BLSTM Framework in Answer Selection
Y Li, M Yang, T Zhao, D Zheng, S Li – National CCF Conference on …, 2017 – Springer
… For the task of sentiment analysis, Huang et al. (2016) used a hierarchical LSTM model to model the retweeting/replying process … A comprehensive view demands further examination of this issue in other NLP tasks such as MT, dialogue system etc …

Personalized question recommendation for English grammar learning
L Fang, LA Tuan, SC Hui, L Wu – Expert Systems – Wiley Online Library
By continuing to browse this site you agree to us using cookies as described in About Cookies. Remove maintenance message …

Toward abstraction from multi-modal data: empirical studies on multiple time-scale recurrent models
J Zhong, A Cangelosi, T Ogata – Neural Networks (IJCNN) …, 2017 – ieeexplore.ieee.org
… element-wise operations. Since it was designed, it has achieved satisfaction results in competitions [7] as well as tasks such as dialogue system [8], sentiment analysis [9] and machine translation [10]. The Gated Recurrent Unit …

ARMENIAN LANGUAGE IN COMPUTATIONAL LINGUISTICS
V Gratian – 2017 – baec.aua.am
… that would be impossible to analyze with human labor. ? Similar to the former are: sentiment analysis and summarization … Extended NLP uses this information to further manipulate language examples of which are machine translation, speech recognition or dialog systems …

Natural language understanding and communication for human-robot collaboration
MI Bloch – ipvs.informatik.uni-stuttgart.de
… of a single sentence, which is semantic parsing, but also analyzing the topic of a text or doing a sentiment analysis of comments to … Considering autonomously working robots with planning abilities, a dialog system makes these robots to co-workers instead of subordinates, as a …

Evaluation of Neural Dialogue Models in Large Domains
M Noseworthy – 2017 – digitool.library.mcgill.ca
… about the news. 1.1 Dialogue System Evaluation Regardless of how a dialogue system is built, it is important to be able to evaluate progress … Page 19. 2 Dialogue System Background In this chapter, we provide a historical overview of the dialogue system literature where …

The Emotional Impact of Audio-Visual Stimuli
TP Thomas – 2017 – search.proquest.com
… Morency. and Mihalcea [28] proposed a multimodal affect (sentiment) analysis model that extracted. text, audio, and video features to help attempt this classification … Bibliography. [1] A. Pak and P. Paroubek, “Twitter as a Corpus for Sentiment Analysis and Opinion …

Hypotheses of Analysis on the Stylistics of Arguments: a Case Study from Trip Advisor
L Bonelli – Argument Technologies – cgi.csc.liv.ac.uk
… Starting from the idea that semantic and expressive levels of argumentation should not be seen as separated instances, this chapter proposes an analytic framework of online sentiment analysis, which mainly focuses on the users’ stylistic and rhetoric choices in a corpus of 100 …

Criticality of Components in Service-Oriented Distributed Systems
DG Design – 2017 – dai-labor.de
… Towards the Automatic Sentiment Analysis of German News and Forum Documents Andreas Lommatzsch, Florian Bütow, Danuta Ploch, Sahin Albayrak In: Proceedings of the 17th I4CS Conference, Darmstadt, Germany; 2017 …

Sequential short-text classification with neural networks
F Dernoncourt – 2017 – dspace.mit.edu
Page 1. Sequential Short-Text Classification MAOT ITUTEl OF TECHNQLOGY with Neural Networks JUN 23 201 by Franck Dernoncourt ARCHiVES Submitted to the Department of Electrical Engineering and Computer Science …

im4Things: An Ontology-Based Natural Language Interface for Controlling Devices in the Internet of Things
JÁ Noguera-Arnaldos, MA Paredes-Valverde… – Current Trends on …, 2017 – Springer
… been successfully applied in domains such as cloud services [10], recommender systems [11], innovation management [12], and sentiment analysis [13], to … On the other hand, Mayordomo [16] is a multimodal (oral, written and a GUI interface) dialogue system focused on the …

Deep Memory Networks for Natural Conversations
??? – 2017 – s-space.snu.ac.kr
… tasks in natural language processing, such as question and answering, machine comprehension and sentiment analysis. Usually attention mechanism requires huge computational cost … 56 [Table 5.4] Test accuracies for sentiment analysis on the Stanford Sentiment …

Multi-sense based neural machine translation
Z Yang, W Chen, F Wang, B Xu – Neural Networks (IJCNN) …, 2017 – ieeexplore.ieee.org
… The newly-emerged multi- sense representation gets increasing interests in NLP area and it has been tested on some NLP tasks, namely artificial word similarity, part of speech tagging, name entity recognition tagging and sentiment analysis [10], [11], [12], [13] …

Discourse Processing in Technology-Mediated Environments
D Gergle – The Routledge Handbook of Discourse Processes, 2017 – books.google.com
… In other words, a mutually beneficial synergy exists whereby computational modeling and technological development can both benefit from, and lead to deeper understanding of, discourse processes. Consider interactive spoken dialogue systems as an example …

Event-based knowledge reconciliation using frame embeddings and frame similarity
M Alam, DR Recupero, M Mongiovi, A Gangemi… – Knowledge-Based …, 2017 – Elsevier
… [33,34] apply Frame Semantics and Distributional Semantics for slot filling in Spoken Dialogue System. In [35], the authors use Word and Frame Embeddings for generating categories of annoying behaviors where each category contains a set of words specific to that category …

Ethical responsibilities of researchers and participants in the development of multimodal interaction corpora
M Koutsombogera, C Vogel – … (CogInfoCom), 2017 8th IEEE …, 2017 – ieeexplore.ieee.org
… our understanding of the way the dialogue is structured and interpret the conversational behavior of the participants, hoping to provide insights to the design of dialogue systems and intelligent … [5] B. Schuller, J.-G. Ganascia, and L. Devillers, “Multimodal sentiment analysis in the …

Multimodal Analysis of User-Generated Multimedia Content
R Shah, R Zimmermann – 2017 – Springer
… manifestations of affect (facial expressions, posture, behavior, physiology), and affective interfaces and applications (dialogue systems, games, learning etc.) … with natural language concepts exploited for tasks such as emotion recognition from text/speech or sentiment analysis …

Affect Aware Ambient Intelligence: Current and Future Directions
C KARYOTIS, F DOCTOR, R IQBAL… – State of the Art in AI …, 2017 – books.google.com
Page 56. State 48 of the Art in AIApplied to Ambient Intelligence A. Aztiria et al.(Eds.) IOS Press, 2017 © 2017 The authors and IOS Press. All rights reserved. doi: 10.3233/978-1-61499-804-4-48 Affect Aware Ambient Intelligence …

EVALITA Goes Social: Tasks, Data
B Pierpaolo, N Malvina, S Rachele… – ITALIAN JOURNAL OF …, 2017 – iris.unito.it
… technologies (see Section 4 for more details). As visible in Figure 1, the 2016 edition featured two re-runs of EVALITA 2014, namely sentiment analysis (SENTIPOLC), and pos tagging (PoSTWITA). However, while the former was an …

Neural Network Architectures for Short Text
D Elliott – 2017 – search.proquest.com
… sumer electronics to large scale data mining systems. More and more businesses are. integrating dialog systems into their products so that their users can enjoy a per … Successful dialog systems. must be able to hold a realistic conversation while helping a user reach their goals …

A Complete Bibliography of ACM Transactions on Asian Language Information Processing
NHF Beebe – 2017 – tug.ctan.org
… Kim:2003:RRE [37] Harksoo Kim and Jungyun Seo. Resolution of referring expressions in a Korean multimodal dialogue system. ACM Transactions on Asian Lan- guage Information Processing, 2(4):324–337, December 2003. CODEN …

Question answering system based on sentence similarity
M Kashif, C Arora – 2017 – repository.iiitd.edu.in
… 5 Page 14. Chapter 3 Semantic Nets and Corpus Statistics 3.1 Introduction Sentence Similarity measures are widely used in text-related research, text-mining, Web page retrieval and dialogue systems. Earlier methods uses long text documents to calculate sentence similarity …

Text Generation Using Different Recurrent Neural Networks
P Taneja, KG Verma – 2017 – dspace.thapar.edu
… They introduced HMM for text generation and compared it with LDA and MC. They experimented different sentiment analysis methods on different data sets and showed that generative models can generate text with a specific sentiment and also concluded that hidden …

Monday, May 15, 2017
SL Datasets, BD Analytics – ieeexplore.ieee.org
Page 1. TECHNICAL PAPERS Scroll to the title and select a Blue link to open a paper. After viewing the paper, use the bookmarks to the left to return to the beginning of the Table of Contents. Monday, May 15, 2017 Session …

End-to-End Trainable Chatbot for Restaurant Recommendations
A Strigér – 2017 – diva-portal.org
… Despite this, it is unclear whether these results would be the same for goal-oriented dialog systems [3] as these kinds of studies do not seem … An example where there are many inputs but only one output is in sentiment analysis, where a sentence is classified as either having a …

COGNIMUSE: a multimodal video database annotated with saliency, events, semantics and emotion with application to summarization
A Zlatintsi, P Koutras, G Evangelopoulos… – EURASIP Journal on …, 2017 – Springer
Research related to computational modeling for machine-based understanding requires ground truth data for training, content analysis, and evaluation. In this paper, we present a multimodal video datab.

A Self-Adaptive Sliding Window Based Topic Model for Non-uniform Texts
J He, L Li, X Wu – Data Mining (ICDM), 2017 IEEE International …, 2017 – ieeexplore.ieee.org
Page 1. A Self-adaptive Sliding Window based Topic Model for Non-uniform Texts Jin He School of Computing and Information HeFei University of Technology Hefei, China, 230009 Email: jinhe@mail.hfut.edu.cn Lei Li School …

Discovering Topic Trends for Conference Analytics
P LIU – 2017 – search.proquest.com
… ods, which bring a recent paradigm shift in natural language processing (NLP), have been successfully adopted in many applications such as word analogy task, named en- tity recognition, machine translation, sentiment analysis, question answering, and so on …

Dealing with the emotions of Non Player Characters
A Baffa, P Sampaio, B Feijó, M Lana – sbgames.org
… Plutchik’s model is often used in computer science in different versions, for tasks such as affective human-computer interaction or sentiment analysis. It is one of the most influential approaches for classifying emotional re- sponses in general[10] …

Sabbiu Shah (070/BCT/531) Sagar Adhikari (070/BCT/533) Samip Subedi (070/BCT/536)
U Chalise – 2017 – researchgate.net
… human would behave as a conversational partner, thereby passing the Turing test. Chatterbots are typically used in dialog systems for various practical purposes including customer service or information acquisition. The classic …

SingularityNET: A decentralized, open market and inter-network for AIs
B Goertzel, S Giacomelli, D Hanson, C Pennachin… – 2017 – icotokn.com
… Image and video processing services, like finding out what people are in a video, or producing a text description of an image; • Language processing services like text summarization, machine translation or text sentiment analysis; …

Long-term knowledge acquisition using contextual information in a memory-inspired robot architecture
F Pratama, F Mastrogiovanni, SG Lee… – Journal of Experimental …, 2017 – Taylor & Francis

Natural Language Processing for Social Media
A Farzindar, D Inkpen – Synthesis Lectures on Human …, 2017 – morganclaypool.com
… Natural Language Processing for Historical Texts Michael Piotrowski 2012 Sentiment Analysis and Opinion Mining Bing Liu 2012 Discourse Processing Manfred Stede 2011 … Spoken Dialogue Systems Kristiina Jokinen and Michael McTear 2009 …

Multilingual extension and evaluation of a poetry generator
HG Oliveira, R Hervás, A Díaz… – Natural Language …, 2017 – cambridge.org
… N-gram- based language models have shown great applicability in many contexts – such as machine translation, speech processing, text prediction or dialog systems – and they present the important advantage of being language independent to a great extent …

Neural network methods for natural language processing
Y Goldberg – Synthesis Lectures on Human Language …, 2017 – morganclaypool.com
… Natural Language Processing for Historical Texts Michael Piotrowski 2012 Sentiment Analysis and Opinion Mining Bing Liu 2012 Discourse Processing Manfred Stede 2011 … Spoken Dialogue Systems Kristiina Jokinen and Michael McTear 2009 …

D1. 4-Final Project Management Report
DB WIT, MT WIT, O Uryupina – cognet.5g-ppp.eu
Page 1. D1.4- Final Project Management Report Document Number D1.4 Status Final Work Package WP 1 Deliverable Type Report Date of Delivery 31/12/2017 Period Covered 1st July 2015 – 31st December 2017 Responsible Unit WIT …

Broad Discourse Context for Language Modeling
M Torres Garcia – 2017 – research-collection.ethz.ch
… An- other example are dialogue systems, where discourse understanding is needed to produce valid utterances for a given conversation context … vectors have become a standard in NLP and are used as input in all sorts of downstream applications such as sentiment analysis …

Helping users learn about social processes while learning from users: developing a positive feedback in social computing
VSS Pillutla – 2017 – search.proquest.com
… 42. 3.6 Sentiment analysis and theme-based clustering using IN-SPIRE. . . . . 43. 3.7 Finding readers arguments that followed the word tax using Jigsaw. . . . . 43. 3.8 Using entity tracking in Jigsaw on the articles. . . . . 44 …

Neural Models for Sequence Chunking.
F Zhai, S Potdar, B Xiang, B Zhou – AAAI, 2017 – aaai.org
Page 1. Neural Models for Sequence Chunking Feifei Zhai, Saloni Potdar, Bing Xiang, Bowen Zhou IBM Watson 1101 Kitchawan Road, Yorktown Heights, NY 10598 {fzhai,potdars,bingxia,zhou}@us.ibm.com Abstract Many …

Progress in Artificial Intelligence: 18th Epia Conference on Artificial Intelligence, Epia 2017, Porto, Portugal, September 5-8, 2017, Proceedings
E Oliveira, J Gama, Z Vale, HL Cardoso – 2017 – books.google.com
Page 1. Eugénio Oliveira· João Gama · Zita Vale Henrique Lopes Cardoso (Eds.) Progress in Artificial Intelligence 18th EPIA Conference on Artificial Intelligence, EPIA 2017 Porto, Portugal, September 5–8, 2017, Proceedings 123 Page 2 …

Argumentation Schemes. History, Classifications, and Computational Applications
F Macagno, D Walton, C Reed – 2017 – papers.ssrn.com
Page 1. Electronic copy available at: https://ssrn.com/abstract=3092491 Argumentation Schemes. History, Classifications, and Computational Applications Fabrizio Macagno Universidade Nova de Lisboa, Portugal fabriziomacagno@hotmail.com …

A novel X-FEM based fast computational method for crack propagation
Z Cheng, H Wang, PMB Vitanyi, N Chater, M Barzegari… – arxiv.org
Attention Submitters: The submission interface will be unavailable due to maintenance for ~2 hours starting 04:00 ET (09:00 UTC) on Thursday, January 18, 2018 …

Towards the Implementation of an Intelligent Software Agent for the Elderly
AHF Dinevari – 2017 – era.library.ualberta.ca
Page 1. Towards the Implementation of an Intelligent Software Agent for the Elderly by Amir Hossein Faghih Dinevari A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science Department of Computing Science University of Alberta …

Linguistic Knowledge Transfer for Enriching Vector Representations
JK Kim – 2017 – rave.ohiolink.edu
Page 1. Linguistic Knowledge Transfer for Enriching Vector Representations DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Joo-Kyung Kim, BE, MS …

A statistical, grammar-based approach to microplanning
C Gardent, L Perez-Beltrachini – Computational Linguistics, 2017 – MIT Press
… content ordering, lexicalization, and aggregation. SPoT is part of a dialog system in the travel domain, which was later on extended to provide restaurant information (SPaRKy; Walker et al. 2007). In this approach, each input …

p. p1 {margin: 0.0 px 0.0 px 0.0 px 0.0 px; font: 24.0 px Helvetica} Social robots powered by IBM Watson as a support for children with health problems
I Kabir, K Kindvall – 2017 – diva-portal.org
Page 1. UPTEC STS 17010 Examensarbete 30 hp Juni 2017 Social robots powered by IBM Watson as a support for children with health problems Isak Kabir Kalle Kindvall Page 2. Teknisk- naturvetenskaplig fakultet UTH-enheten …

A Qualitative GIS for Social Media and Big Data
ME Martin – 2017 – summit.sfu.ca
… Page 17. 6 or conversation. It has been used in several applications by GIScientists including obesity and tourism (Ghosh and Guha, 2013; Hao et al., 2010). Sentiment analysis is an up and coming NLP technique that can be used to determine the emotions of text and …

Annotation of semantic roles for the Turkish Proposition Bank
GG ?ahin, E Adal? – Language Resources and Evaluation – Springer
… Finally, we conclude in Sect. 8. 2 Related work Crowdsourcing approaches have recently been harnessed to annotate, evaluate and create corpora (Mohammad and Turney 2013; Basile et al. 2012) for different NLP problems such as sentiment analysis (Mellebeek et al …

A multi-agent framework to support user-aware conversational agents In an e-learning environment
M Procter – 2017 – dt.athabascau.ca
Page 1. ATHABASCA UNIVERSITY A MULTI-AGENT FRAMEWORK TO SUPPORT USER-AWARE CONVERSATIONAL AGENTS IN AN E-LEARNING ENVIRONMENT BY MICHAEL PROCTER A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES …

Question-based Text Summarization
M Liu – 2017 – search.proquest.com
Question-based Text Summarization. Abstract. In the modern information age, finding the right information at the right time is an art (and a science). However, the abundance of information makes it difficult for people to digest it and make informed choices …

Interacting with recommenders—overview and research directions
M Jugovac, D Jannach – ACM Transactions on Interactive Intelligent …, 2017 – dl.acm.org
Page 1. 10 Interacting with Recommenders—Overview and Research Directions MICHAEL JUGOVAC and DIETMAR JANNACH, TU Dortmund Automated recommendations have become a ubiquitous part of today’s online user experience …

Deep Reinforcement Learning in Natural Language Scenarios
J He – 2017 – digital.lib.washington.edu
… Many artificial intelligence tasks involve sequential decision making and delayed rewards, such as video gaming, human-computer dialogue systems, newsfeed recommendation, and … computer or human-robot dialog systems, the agent needs to understand the dialog state …

Design and development of a cognitive assistant for the architecting of earth observing satellites
A Virós Martin – 2017 – upcommons.upc.edu
Page 1. DDC AAE OS by Antoni Virós Martin September 2017 Submitted to the faculty of the Barcelona School of Informatics (FIB) of Universitat Politècnica de Catalunya (UPC) – BarcelonaTech in Partial Fulfillment of the Requirements for the …

HCI International 2017–Posters’ Extended Abstracts: 19th International Conference, HCI International 2017, Vancouver, BC, Canada, July 9–14, 2017 …
C Stephanidis – 2017 – books.google.com
… 450 Junko Itou, Rina Tanaka, and Jun Munemori Collection of Example Sentences for Non-task-Oriented Dialog Using a Spoken Dialog System and Comparison with Hand-Crafted DB … Page 18. Contents – Part I XXI End-to-End Dialogue with Sentiment Analysis Features …

Taking IS history seriously
NR Hassan – The Routledge Companion to Management …, 2017 – content.taylorfrancis.com
Page 1. Introduction The development, adoption and use of information systems (IS) in and across organisations has arguably been a major focus of research in MIS (Córdoba, et al., 2012). This part, thus, offers an insightful …

Automatic Text Simplification
H Saggion – Synthesis Lectures on Human Language …, 2017 – morganclaypool.com
… Natural Language Processing for Historical Texts Michael Piotrowski 2012 Sentiment Analysis and Opinion Mining Bing Liu 2012 Discourse Processing Manfred Stede 2011 … Spoken Dialogue Systems Kristiina Jokinen and Michael McTear 2009 …

Computational models for semantic textual similarity
A González Aguirre – 2017 – addi.ehu.es
Page 1. UNIVERSITY OF THE BASQUE COUNTRY Computer Languages and Systems PhD Thesis Computational Models for Semantic Textual Similarity Aitor Gonzalez-Agirre 2017 (c)2017 AITOR GONZALEZ AGIRRE Page 2. Page 3 …

Natural Language Processing and Computational Linguistics 2: Semantics, Discourse and Applications
MZ Kurdi – 2017 – books.google.com
Page 1. COGNITIVE SCIENCE SERIES Natural Language Processing and Computational Linguistics 2 Semantics, Discourse and Applications Mohamed zakaria Kurdi Page 2. COGNITIVE SCIENCE SERIES | I. Page 3. Page 4 …

Sequential modeling, generative recurrent neural networks, and their applications to audio
S Mehri – 2017 – papyrus.bib.umontreal.ca
Page 1. Université de Montréal Sequential Modeling, Generative Recurrent Neural Networks, and Their Applications to Audio par Soroush Mehri Département d’informatique et de recherche opérationnelle Faculté des arts et des sciences …

Narrative Information Extraction with Non-Linear Natural Language Processing Pipelines
JV Vargas – 2017 – search.proquest.com
… the. text such as question answering, dialog systems, paraphrasing or automatic summarization still. pose important problems … resolution. system, and the sentiment analysis tools, and provides model files for processing English text …

Automated Feature Engineering for Deep Neural Networks with Genetic Programming
J Heaton – 2017 – search.proquest.com
… A SOM allowed M. Wang et al. (2016) to identify the mixtures of Chinese herbal medicines. Sobkowicz. 39. (2016) implemented a NEAT neural network to perform sentiment analysis in the Polish language. Deep Learning. While …

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