Semantic Textual Similarity & Dialog Systems 2019


Notes:

Semantic textual similarity measures the degree of semantic equivalence between two texts.

  • Corpus similarity
  • Document similarity
  • Semantic similarity
  • Text similarity
  • Textual similarity

Wikipedia:

See also:

Semantics


Training neural response selection for task-oriented dialogue systems
M Henderson, I Vuli?, D Gerz, I Casanueva… – arXiv preprint arXiv …, 2019 – arxiv.org
… Abstract Despite their popularity in the chatbot liter- ature, retrieval-based models have had mod- est impact on task-oriented dialogue systems, with the main obstacle to their application be- ing the low-data regime of most task-oriented dialogue tasks …

Sentence Similarity Techniques for Short vs Variable Length Text using Word Embeddings
D Shashavali, V Vishwjeet, R Kumar, G Mathur… – Computación y …, 2019 – cys.cic.ipn.mx
… Fig. 1. The primary goal of the dialogue systems is to understand the user’s input or goal by using NLU techniques, the bot must manage to … In Chatbot application, False Positive must be very less for better user experience … Learning semantic textual similarity from conversations …

Debbie, the debate bot of the future
G Rakshit, KK Bowden, L Reed, A Misra… – … Social Interaction with …, 2019 – Springer
… 1: proceedings of the main conference and the shared task: semantic textual similarity, Vol 1 … J (2016) ZIB structure prediction pipeline: how NOT to evaluate your dialogue system: an empirical … Toda T, Adriani M, Nakamura S (2014) Developing non-goal dialog system based on …

A Content Management System for Chatbots
B Galitsky – Developing Enterprise Chatbots, 2019 – Springer
… Also, there is a unique set of restrictions and user needs associated with chatbot content. Nowadays, developers are using legacy tools and repurposing or retrofitting legacy content into chatbots, so in a lot of cases users are unimpressed …

Investigating the effects of word substitution errors on sentence embeddings
R Voleti, JM Liss, V Berisha – ICASSP 2019-2019 IEEE …, 2019 – ieeexplore.ieee.org
… include sentiment analysis of product reviews, customer service chatbots, biomedical informatics … An integrated dialog simulation technique for evaluating spoken dialog systems,” in Coling … and Lucia Specia, “SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and …

Semantic similarity modeling based on multi-granularity interaction matching
X Li, C Yao, Q Zhang, G Zhang – International Journal of Innovative …, 2019 – ijicic.org
… In the question answering and dialogue system, the user’s input is very casual and colloquial. Paraphrase identification technology can match the user’s questions to the standard questions and improve the recall of answer extraction …

Novel Approach towards Arabic Question Similarity Detection
M Daoud – 2019 2nd International Conference on new Trends …, 2019 – ieeexplore.ieee.org
… 49–56. [7] A. Islam, “Semantic text similarity using corpus-based word similarity and string similarity,” ACM Trans. Knowl. Discov … Trademark Off., 2018. [11] NM Radziwill and MC Benton, “Evaluating Quality of Chatbots and Intelligent Conversational Agents,” Apr. 2017 …

ONE-SHOT OF WINE: DEEP LEARNING ARCHITECTURES FOR DIFFERENT SETTINGS OF THE SENTENCE SIMILARITY PROBLEM
T Knowles, T Wu – cs229.stanford.edu
… We note that there are (at least) two settings of this problem: in setting 1, we can enumerate all possible labels that a sentences may take on (such as the user intentions in a chat-bot) and have training data associated with … Learning semantic textual similarity from conversations …

Lifelong learning and task-oriented dialogue system: what does it mean?
M Veron, S Ghannay, AL Ligozat, S Rosset – 2019 – hal.archives-ouvertes.fr
… 2. It searches in unstructured data by estimating semantic textual similarity, if the user asks a question relative to … Lifelong learning and task-oriented dialogue system: what does it mean … In Tenth International Work- shop on Spoken Dialogue Systems Technology (IWSDS), 2019 …

From Lexical to Semantic Features in Paraphrase Identification
P Fialho, L Coheur, P Quaresma – 8th Symposium on Languages …, 2019 – drops.dagstuhl.de
… scope of the demonstration project AIA, “Apoio Inteligente a empreendedores (chatbots)”, which also … In addition, paraphrase identification can also be used by a chatbot that has … corpora, and apply the same approach to the tasks of Semantic Textual Similarity and Recognizing …

A Markov Network Model for Natural Language Semantic Matching
L Wang, T Bui, F Dernoncourt… – … Conference on Data …, 2019 – ieeexplore.ieee.org
… because it has been used by many real-world NLP systems (eg, intelligent personal assistants, question answering, and dialogue systems) … Neural Network Models for Paraphrase Identification, Semantic Textual Similarity, Natural Language Inference, and Question Answering …

Sentence Similarity Computation in Question Answering Robot
S Si, W Zheng, L Zhou, M Zhang – Journal of Physics: Conference …, 2019 – iopscience.iop.org
… The findings in this research are very useful to the development of chatbots in Zhiyan Technology (Shenzhen) Limited. References [1] Kenter, T. and De Rijke, M., 2015, October … Semantic text similarity using corpus-based word similarity and string similarity. TKDD, 2008 …

Learning Discourse-Level Structures for Question Answering
B Galitsky – Developing Enterprise Chatbots, 2019 – Springer
… Developing Enterprise Chatbots pp 177-219 | Cite as. Learning Discourse-Level Structures for Question Answering … Passage re-ranking improvement via parse thickets is evaluated in a variety of chatbot question-answering domains with long questions …

Multilingual Question Answering from Formatted Text applied to Conversational Agents
W Siblini, C Pasqual, A Lavielle, C Cauchois – arXiv preprint arXiv …, 2019 – arxiv.org
… Applied in a real-world situation in chatbots, first results indicate that it allows the conversational process to … With the cross-lingual question answering, the chatbot can explore any content and may find a potential … Semeval-2012 task 6: A pilot on semantic textual similarity …

Efficient answer-annotation for frequent questions
M Zlabinger, N Rekabsaz, S Zlabinger… – … Conference of the Cross …, 2019 – Springer
… 3 Text Similarity Methods. In this section, we summarize unsupervised semantic text similarity methods … The questions originate from a chat-bot system that maps questions to an answer set, namely a static set of Frequently Asked Questions (FAQ) …

Knowledge Acquisition and Corpus for Argumentation-Based Chatbots
LA Chalaguine, A Hunter – 2019 – ceur-ws.org
… Chatbots that do make use of argumentation, usually assume an existing knowledge base where the counterarguments … Impact of argument type and concerns in argumentation with a chatbot … Identifying prominent arguments in online debates using semantic textual similarity …

A Study of Incorrect Paraphrases in Crowdsourced User Utterances
MA Yaghoub-Zadeh-Fard, B Benatallah… – Proceedings of the …, 2019 – aclweb.org
… Also known as dialogue systems, virtual assistants, chatbots or simply bots (Campagna et al., 2017; Su et al., 2017 … Moreover, it is feasible to automatically generate pairs of questions and answers by mining datasets in the fields of Question Answering and dialog systems …

Deep Contextualized Pairwise Semantic Similarity for Arabic Language Questions
H Al-Bataineh, W Farhan, A Mustafa, H Seelawi… – arXiv preprint arXiv …, 2019 – arxiv.org
… In this work, we are focusing one Semantic Textual Similarity (STS) of a question pair with the main assumption that if two questions have the … Digital assistants like chat-bots or voice assistants also need such NLU model to map the user question to already indexed answered …

Using Lucene for Developing a Question-Answering Agent in Portuguese
H Gonçalo Oliveira, R Filipe… – 8th Symposium on …, 2019 – drops.dagstuhl.de
… Since ELIZA, chatbots and dialog systems have become more human … This can be achieved, for instance, with a regression model that considers several lexical or semantic features to measure semantic textual similarity [5]. As opposed to the generative approach, IR-based …

A repository of conversational datasets
M Henderson, P Budzianowski, I Casanueva… – arXiv preprint arXiv …, 2019 – arxiv.org
… Page 7. Hongshen Chen, Xiaorui Liu, Dawei Yin, and Jiliang Tang. 2017. A survey on dialogue systems: Recent advances and new frontiers. CoRR, abs/1711.01731 … Ahmed Fadhil and Gianluca Schiavo. 2019. Designing for health chatbots. CoRR, abs/1902.09022 …

Discourse-Level Dialogue Management
B Galitsky – Developing Enterprise Chatbots, 2019 – Springer
… The workhorse of traditional dialog systems is slot-filling (Wang and Lemon 2013) which … 11.3.8 Evaluation: Information Access Efficiency in Chatbots Versus Search Engines … Twelve users (author’s colleagues) asked the chatbot 15–20 questions reflecting their financial …

Enhanced answer selection in CQA using multi-dimensional features combination
H Fan, Z Ma, H Li, D Wang, J Liu – Tsinghua Science and …, 2019 – ieeexplore.ieee.org
Page 1. TSINGHUA SCIENCE AND TECHNOLOGY ISSNll1007-0214 09/10 pp346–359 DOI: 10.26599/TST.2018.9010050 Volume 24, Number 3, June 2019 Enhanced Answer Selection in CQA Using Multi-Dimensional Features Combination …

Distributional Models with Syntactic Contexts for the Measurement of Word Similarity in Brazilian Portuguese
EE Berlitz, DA Araujo, AB Silva, RR Righi, SJ Rigo – 2019 – researchgate.net
… 2009). Better techniques for identifying word similarity can help in many NLP tasks such as dialogue systems, question answering and information retrieval systems (Agirre et al., 2009; Pilehvar et al., 2013; Oliveira, 2018). Historically …

Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
R Mitkov, G Angelova – Proceedings of the International Conference on …, 2019 – aclweb.org
… Ilvovsky . . . . . 373 On a Chatbot Providing Virtual Dialogues Boris Galitsky, Dmitry Ilvovsky and Elizaveta Goncharova . . . . . 382 Assessing …

An Urdu semantic tagger-lexicons, corpora, methods and tools
J Shafi – 2019 – eprints.lancs.ac.uk
… [65], software engineering [227], empirical language analysis [171], requirements engineering [182], historical semantic analysis via HTST 1.1 [166], to train a Chatbot [218], and several others [23, 214]. Moreover, USAS [180] has been ported previously …

Measuring interpretable semantic similarity of sentences using a multi chunk aligner
G Majumder, P Pakray, D Pinto – Journal of Intelligent & Fuzzy …, 2019 – content.iospress.com
… G. , Uriaa L. and Wiebe J. , Semeval-2015 task 2: Semantic textual similarity, english, Spanish … and Koedinger KR , Pedagogical content knowledge in a tutorial dialogue system to support … explanation, Working Notes of the AIED 2001 Workhop Tutorial Dialogue Systems (2001) …

Cross-lingual Semantic Specialization via Lexical Relation Induction
EM Ponti, I Vuli?, G Glavaš, R Reichart… – Proceedings of the 2019 …, 2019 – aclweb.org
… constraints. We prove the effectiveness of our method through intrinsic word similarity evaluation in 8 lan- guages, and with 3 downstream tasks in 5 languages: lexical simplification, dialog state tracking, and semantic textual similarity …

Unified language model pre-training for natural language understanding and generation
L Dong, N Yang, W Wang, F Wei, X Liu… – Advances in Neural …, 2019 – papers.nips.cc
… [5] Daniel Cer, Mona Diab, Eneko Agirre, Inigo Lopez-Gazpio, and Lucia Specia. Semeval-2017 task 1: Semantic textual similarity-multilingual and cross-lingual focused evaluation … In AAAI Dialog System Technology Challenges Workshop, 2019 …

ConveRT: Efficient and Accurate Conversational Representations from Transformers
M Henderson, I Casanueva, N Mrkši?, PH Su… – arXiv preprint arXiv …, 2019 – arxiv.org
… 1 Introduction Dialog systems, also referred to as conversational systems or conversational agents, have found use in a wide range of applications … Page 3. portunities for more researchers and practition- ers to tap into the construction of neural task- based dialog systems …

Comparison of transfer-learning approaches for response selection in multi-turn conversations
J Vig, K Ramea – Workshop on DSTC7, 2019 – pdfs.semanticscholar.org
… to response selection in dialogs, as part of the Dialog System Technology Challenge … been conducted since 2013 to advance the state of the art in dialog systems … Neural network models for paraphrase identification, semantic textual similarity, natu- ral language inference, and …

Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)
M Bansal, A Villavicencio – Proceedings of the 23rd Conference on …, 2019 – aclweb.org
… Fully Unsupervised Crosslingual Semantic Textual Similarity Metric Based on BERT for Identifying Parallel Data Chi-kiu Lo and Michel Simard … Incorporating Interlocutor-Aware Context into Response Generation on Multi-Party Chatbots Cao Liu, Kang Liu, Shizhu He, Zaiqing …

Skip Act Vectors: integrating dialogue context into sentence embeddings
J Auguste, F Béchet, G Damnati, D Charlet – 2019 – hal.archives-ouvertes.fr
… Tenth International Workshop on Spoken Dialogue Systems Technology, Apr 2019, Syracuse, Italy … turn is of great practical use in applications such as automated dialog system for predicting … R., Rigau, G., Wiebe, J.: Semeval-2014 task 10: Multilingual semantic textual similarity …

Unsupervised post-processing of word vectors via conceptor negation
T Liu, L Ungar, J Sedoc – Proceedings of the AAAI Conference on Artificial …, 2019 – aaai.org
… Semantic Textual Similarity In this subsection, we show- case the effectiveness of the proposed post-processing method using semantic textual similarity (STS) benchmarks, which are designed to test the semantic similarities of sen- tences …

Design and Implementation of Intelligent Medical Customer Service Robot Based on Deep Learning
P GUO, WEI DENG – … on Wavelet Active Media Technology and …, 2019 – ieeexplore.ieee.org
… Contextual consistency is an important feature to reflect intelligence for dialogue system … The sentence embedding created from the model performs well on Semantic Text Similarity (STS) benchmark and the SemEval2017 Community Q&A (CQA) problem similarity subtask …

Multi-Lingual Dialogue Act Recognition with Deep Learning Methods
J Martínek, P Kral, L Lenc, C Cerisara – arXiv preprint arXiv:1904.05606, 2019 – arxiv.org
… understand- ing and it plays a pivotal role in dialogue management [4]. Any improvement in this task may increase the performance of the whole dialogue system … Dialog Systems … [28] T. Brychc?n, “Linear transformations for cross-lingual semantic textual similarity,” arXiv preprint …

Love in Lyrics: An Exploration of Supporting Textual Manifestation of Affection in Social Messaging
T Kim, JS Lee, Z Peng, X Ma – Proceedings of the ACM on Human …, 2019 – dl.acm.org
Page 1. 79 Love in Lyrics: An Exploration of Supporting Textual Manifestation of Affection in Social Messaging TAEWOOK KIM, Hong Kong University of Science and Technology, Hong Kong SAR JUNG SOO LEE, Korea University …

Model Comparison for Semantic Grouping
F Vargas, K Brestnichki, N Hammerla – arXiv preprint arXiv:1904.13323, 2019 – arxiv.org
… The problem of Semantic Textual Similarity (STS), measur- ing how closely the meaning of one piece of … settings are both practical and key to use-cases that involve information retrieval in dialogue systems. For ex- ample, in a chat-bot application new queries will arrive one at a …

An Empirical Evaluation Of Attention And Pointer Networks For Paraphrase Generation
V Gupta – 2019 – spectrum.library.concordia.ca
… cation of sentences, summarizing paragraphs, information retrieval, information ex- traction, restating utterances generated by a conversational agent ChatBots to map student vocabulary … In conversational agent systems also known as chat-bots, paraphrases are used to …

Linguistic classification: dealing jointly with irrelevance and inconsistency
L Franzoi, A Sgarro, A Dinu, LP Dinu – 12th International Conference on …, 2019 – arts.units.it
… Ilvovsky . . . . . 373 On a Chatbot Providing Virtual Dialogues Boris Galitsky, Dmitry Ilvovsky and Elizaveta Goncharova . . . . . 382 Assessing …

Neural Network Models for Text Understanding
L Zhang – 2019 – utd-ir.tdl.org
… texts, and (3) make inference from the texts to generate solutions for high-level tasks, such as Semantic Relation Extraction, Textual Entailment, Semantic Textual Similarity, Sentiment Analysis, Dialog Systems, Question Answering (QA) etc. This problem has been tradition …

RIPPED: Recursive Intent Propagation using Pretrained Embedding Distances
M Ball – 2019 – cs.brown.edu
… 1https://www.drift.com/chatbots/ 2Google trends reports a 10-fold increase in … For example, consider building a medical chatbot, or designing a virtual legal assistant … we use for this evaluation can be categorised into three main groups: semantic-textual similarity (STS), inference …

Moverscore: Text generation evaluating with contextualized embeddings and earth mover distance
W Zhao, M Peyrard, F Liu, Y Gao, CM Meyer… – arXiv preprint arXiv …, 2019 – arxiv.org
… It is particularly important for a metric to not only capture the amount of shared content between two texts, ie, intersect(A,B), as is the case with many semantic textual similarity measures (Peters et al., 2018; Devlin et al., 2018); but also to accurately reflect to what extent the …

Leveraging sentence similarity in natural language generation: Improving beam search using range voting
S Borgeaud, G Emerson – arXiv preprint arXiv:1908.06288, 2019 – arxiv.org
… This opens up many other tasks, including machine translation, summarisa- tion, dialogue systems, and question answering … 2017. SemEval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation …

Arabic Text Semantic Graph Representation
WM Al Etaiwi, A Awajan – 2019 2nd International Conference …, 2019 – ieeexplore.ieee.org
… The proposed model is used to enhance human-machine Spoken Dialogue System (SDS). In which, the fairly constrained semantic space is limited … [15] M. AL-Smadi, Z. Jaradat, M. AL-Ayyoub, and Y. Jararweh, “Paraphrase identification and semantic text similarity analysis in …

Reliable Classification of FAQs with Spelling Errors Using an Encoder-Decoder Neural Network in Korean
Y Jang, H Kim – Applied Sciences, 2019 – mdpi.com
… Frequently asked questions (FAQs) in commercial services based on social media (eg, chatbot for online banking) accommodate both … In sentence classification tasks such as sentiment analysis and semantic textual similarity analysis, BERT also outperformed the previous state …

Commonsense reasoning for natural language understanding: A survey of benchmarks, resources, and approaches
S Storks, Q Gao, JY Chai – arXiv preprint arXiv:1904.01172, 2019 – researchgate.net
Page 1. COMMONSENSE REASONING FOR NATURAL LANGUAGE UNDERSTANDING: ASURVEY Commonsense Reasoning for Natural Language Understanding: A Survey of Benchmarks, Resources, and Approaches Shane Storks STORKSSH@MSU.EDU Qiaozi Gao …

Automatically responding to customers
R Huijzer – pure.tue.nl
… The IBM sales department claims that Autodesk using chatbots cut down their resolution … Conversational agent or dialogue systems aim to communicate with humans using natural lan- guage. Consensus is not clear on whether a chatbot is synonymous to conversational agent …

Automated Approaches to Community Question Answering
A Uva – 2019 – eprints-phd.biblio.unitn.it
… The latter can be used to quickly bootstrap Natural Language Understanding pipelines for dialog systems. To conclude, we study advantages and disadvantages of neural networks and tree kernel models when applied to cQA tasks …

BI-GRU Capsule Networks for Student Answers Assessment
NA Khayi, V Rus – 2019 KDD Workshop on Deep Learning for Education …, 2019 – ml4ed.cc
… (2018) proposed an Attention Siamese Long Short-Term Memory (LSTM) model to measure the semantic textual similarity … Our task of automatically assessing freely generated student answers within a dialog system context is a special case of the more general semantic …

Development and deployment of a large-scale dialog-based intelligent tutoring system
S Afzal, T Dhamecha, N Mukhi… – Proceedings of the …, 2019 – eprints.qut.edu.au
… Student Response Analysis (SRA) is the task of labeling student answers with categories that can help a dialog system to generate appropriate and effective feedback on errors … Semeval-2012 task 6: A pilot on semantic textual similarity. In SemEval-2012, pages 385–393. ACL …

ReQA: An Evaluation for End-to-End Answer Retrieval Models
A Ahmad, N Constant, Y Yang, D Cer – arXiv preprint arXiv:1907.04780, 2019 – arxiv.org
… 2019. Training neural response selection for task-oriented dialogue systems. arXiv preprint arXiv:1906.01543. Mandar Joshi, Eunsol Choi, Daniel S. Weld, and Luke Zettlemoyer. 2017 … 2018. Learning semantic textual similarity from conversations …

Queens are Powerful too: Mitigating Gender Bias in Dialogue Generation
E Dinan, A Fan, A Williams, J Urbanek, D Kiela… – arXiv preprint arXiv …, 2019 – arxiv.org
… Pineau. 2018. Ethical challenges in data-driven dialogue systems. In Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, AIES 2018, New Orleans, LA, USA, Febru- ary 02-03, 2018, pages 123–129. Alexander …

A narrative sentence planner and structurer for domain independent, parameterizable storytelling
SM Lukin, MA Walker – Dialogue & Discourse, 2019 – 129.70.43.92
… Natural Language and Dialogue Systems Lab University of California, Santa Cruz, CA … New evaluations are presented that measure the quality of the baseline translation algorithm in terms of text similarity, semantic text similarity, fluency, and grammaticality …

The Dialogue Dodecathlon: Open-Domain Knowledge and Image Grounded Conversational Agents
K Shuster, D Ju, S Roller, E Dinan, YL Boureau… – arXiv preprint arXiv …, 2019 – arxiv.org
Page 1. The Dialogue Dodecathlon: Open-Domain Knowledge and Image Grounded Conversational Agents Kurt Shuster, Da Ju, Stephen Roller Emily Dinan, Y-Lan Boureau, Jason Weston Facebook AI Research Abstract We …

On the integration of conceptual hierarchies with deep learning for explainable open-domain question answering
H Tayyar Madabushi – 2019 – etheses.bham.ac.uk
… 45 3.6.1 An Introduction to the Task of Semantic Text Similarity … that are to be answered by the chatbot. However, chatbots additionally require techniques of extending conversations with users, motivating further interaction and other elements of human-human talk …

Simple and Effective Monolingual and Code-Mixed Question Answering
V Gupta – 2019 – web2py.iiit.ac.in
… Raghavi et al. [22] also highlight the prevalence of CM in conversations with a chatbot built for users in India. Code-mixing and code-switching has recently gathered much attention from researchers [14, 66, 64, 63, 11, 31, 15] …

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume …
J Burstein, C Doran, T Solorio – Proceedings of the 2019 Conference of …, 2019 – aclweb.org
Page 1. NAACL HLT 2019 The 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies Proceedings of the Conference Vol. 1 (Long and Short Papers) June 2 – June 7, 2019 Page 2 …

Importance of Search and Evaluation Strategies in Neural Dialogue Modeling
I Kulikov, A Miller, K Cho, J Weston – Proceedings of the 12th …, 2019 – aclweb.org
… These results highlight both the importance of search algorithms as well as the dif- ficulty in evaluating neural dialogue systems in a realistic, full conversation setup. We will make trained models, code and human evaluation transcripts publicly available …

Incremental Domain Adaptation for Neural Machine Translation in Low-Resource Settings
M Kalimuthu, M Barz, D Sonntag – … of the Fourth Arabic Natural Language …, 2019 – aclweb.org
Page 1. Proceedings of the Fourth Arabic Natural Language Processing Workshop, pages 1–10 Florence, Italy, August 1, 2019. c 2019 Association for Computational Linguistics 1 Incremental Domain Adaptation for Neural Machine Translation in Low-Resource Settings …

Superglue: A stickier benchmark for general-purpose language understanding systems
A Wang, Y Pruksachatkun, N Nangia… – Advances in Neural …, 2019 – papers.nips.cc
Page 1. SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems Alex Wang? New York University Yada Pruksachatkun? New York University Nikita Nangia? New York University Amanpreet …

Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches
S Storks, Q Gao, JY Chai – arXiv preprint arXiv:1904.01172, 2019 – researchgate.net
Page 1. RECENT ADVANCES IN NATURAL LANGUAGE INFERENCE:ASURVEY Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches Shane Storks SSTORKS@UMICH.EDU …

Learning Outcomes and Their Relatedness in a Medical Curriculum
S Mondal, T Dhamecha, S Godbole, S Pathak… – Proceedings of the …, 2019 – aclweb.org
… textual content. There is a parallel thread of work on Semantic Textual Similarity (STS), which measures the de- gree of equivalence in the underlying semantics of paired snippets of text (Agirre et al., 2015, 2016, 2012). This …

Stylistic Control for Neural Natural Language Generation
S Oraby – 2019 – escholarship.org
Page 1. UC Santa Cruz UC Santa Cruz Electronic Theses and Dissertations Title Stylistic Control for Neural Natural Language Generation Permalink https://escholarship.org/uc/item/54p9r87q Author Oraby, Shereen Publication Date 2019 Peer reviewed|Thesis/dissertation …

Survey on frontiers of language and robotics
T Tangiuchi, D Mochihashi, T Nagai, S Uchida… – Advanced …, 2019 – Taylor & Francis
Page 1. ADVANCED ROBOTICS 2019, VOL. 33, NOS. 15–16, 700–730 https://doi.org/10.1080/01691864.2019.1632223 SURVEY PAPER Survey on frontiers of language and robotics T. Tangiuchia, D. Mochihashib,c, T. Nagai …

Understanding Chat Messages for Sticker Recommendation in Messaging Apps
A Laddha, M Hanoosh, D Mukherjee, P Patwa… – aaai.org
Page 1. Understanding Chat Messages for Sticker Recommendation in Messaging Apps Abhishek Laddha, Mohamed Hanoosh, Debdoot Mukherjee, Parth Patwa, Ankur Narang Hike Messenger {abhishekl, moh.hanoosh, debdoot, parthp, ankur}@hike.in Abstract …

Fixed That for You: Generating Contrastive Claims with Semantic Edits
C Hidey, K McKeown – Proceedings of the 2019 Conference of the North …, 2019 – aclweb.org
Page 1. Proceedings of NAACL-HLT 2019, pages 1756–1767 Minneapolis, Minnesota, June 2 – June 7, 2019. c 2019 Association for Computational Linguistics 1756 Fixed That for You: Generating Contrastive Claims with Semantic Edits …

End-to-end Neural Information Retrieval
W Yang – 2019 – uwspace.uwaterloo.ca
Page 1. End-to-end Neural Information Retrieval by Wei Yang A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Master in Computer Science Waterloo, Ontario, Canada, 2019 c Wei Yang 2019 Page 2 …

Towards the Automatic Classification of Student Answers to Open-ended Questions
JG Alvarado Mantecon – 2019 – ruor.uottawa.ca
Page 1. Towards the Automatic Classification of Student Answers to Open-ended Questions by Jesus Gerardo Alvarado Mantecon Thesis submitted to the University of Ottawa in partial fulfilment of the requirements for the Master of Computer Science degree …

A Heuristically Modified FP-Tree for Ontology Learning with Applications in Education
S Shatnawi, MM Gaber, M Cocea – arXiv preprint arXiv:1910.13561, 2019 – arxiv.org
… answers on a subset of questions and their ratings were used to identify the most appropriate automatic semantic text similarity metric to … for various pur- poses such as instructional design [37], adaptive intelligent educational systems [34], tutorial dialog systems [27], assessment …

Controllable Paraphrase Generation with a Syntactic Exemplar
M Chen, Q Tang, S Wiseman, K Gimpel – arXiv preprint arXiv:1906.00565, 2019 – arxiv.org
… particular types of queries (Kumar et al., 2017). It can also bear on dialogue systems that seek to generate utterances that fit particular functional categories (Ke et al., 2018; Li et al., 2019). To address this task, we propose a …

Generalizing Natural Language Analysis through Span-relation Representations
Z Jiang, W Xu, J Araki, G Neubig – arXiv preprint arXiv:1911.03822, 2019 – arxiv.org
Page 1. GENERALIZING NATURAL LANGUAGE ANALYSIS THROUGH SPAN-RELATION REPRESENTATIONS Zhengbao Jiang Language Technologies Institute Carnegie Mellon University zhengbaj@cs.cmu.edu Wei Xu …

CoaCor: code annotation for code retrieval with reinforcement learning
Z Yao, JR Peddamail, H Sun – The World Wide Web Conference, 2019 – dl.acm.org
Page 1. CoaCor: Code Annotation for Code Retrieval with Reinforcement Learning Ziyu Yao The Ohio State University yao.470@osu.edu Jayavardhan Reddy Peddamail The Ohio State University peddamail.1@osu.edu Huan Sun The Ohio State University sun.397@osu.edu …

Multitask learning approach for understanding the relationship between two sentences
HS Choi, H Lee – Information Sciences, 2019 – Elsevier
… Semantic textual similarity (STS) is the task of measuring the degree to which two sentences are semantically similar with each … tasks have been leveraged for applications such as document summarization, text generation, semantic search, dialog system, question answering …

Deep Dialog Act Recognition using Multiple Token, Segment, and Context Information Representations
E Ribeiro, R Ribeiro, DM de Matos – Journal of Artificial Intelligence …, 2019 – jair.org
… also taken into account. However, when the discourse model is based on a CNN or on a bidirectional LSTM unit, it considers information from future segments, which is not available to a dialog system. Still, even when relying …

Deep Neural Networks for Selected Natural Language Processing Tasks
J Martínek – 2019 – dspace5.zcu.cz
Page 1. University of West Bohemia Department of Computer Science And Engineering Univerzitni 22 306 14 Plzen Czech Republic Deep Neural Networks for Selected Natural Language Processing Tasks PhD Study Report Ing. Jirí Martínek Technical Report No …

Incorporating domain knowledge into natural language inference on clinical texts
M Lu, Y Fang, F Yan, M Li – IEEE Access, 2019 – ieeexplore.ieee.org
Page 1. 2169-3536 (c) 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org …

Collective memory shapes the organization of individual memories in the medial prefrontal cortex}}
P Gagnepain, T Vallée, S Heiden, M Decorde… – Nature – perso.limsi.fr
… retrieval; Example-based dialogue modelling; Open-domain dialogue system; Evaluation}, } @inproceedings … Interaction}}, booktitle = {{International Workshop on Spoken Dialogue Systems}}, year = {2016 … Agent}}, booktitle = {{Second Workshop on Chatbots and Conversational …

The evolution of argumentation mining: From models to social media and emerging tools
A Lytos, T Lagkas, P Sarigiannidis… – Information Processing & …, 2019 – Elsevier
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Semantic Feature Extraction Using Multi-Sense Embeddings and Lexical Chains
TL Ruas – 2019 – deepblue.lib.umich.edu
Page 1. Semantic Feature Extraction Using Multi-Sense Embeddings and Lexical Chains by Terry L. Ruas A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Computer and …

Enabling deaf or hard of hearing accessibility in live theaters through virtual reality
MRS Teófilo – 2019 – tede.ufam.edu.br
… Technologies as Automatic Speech Recognition (ASR), Sentence Prediction (SP), Semantic Textual Similarity (STS), which was used to Speech … or conversing with speech dialogue systems, is relatively easy. Recognizing the speech of two Page 23. Chapter 2. Background 22 …

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