Treebank & Chatbots 2020


Notes:

A treebank is a parsed text corpus that annotates syntactic or semantic sentence structure.

Wikipedia:

See also:

100 Best Decision Tree Videos | 100 Best TreeMap Videos | AST (Abstract Syntax Tree) & Dialog Systems | Conversation TreesDecision Tree Classifier & Dialog Systems | Grammar Trees & Dialog Systems | Rhetorical Structure TreeStanford Tregex


IntelliBot: A Dialogue-based chatbot for the insurance industry
M Nuruzzaman, OK Hussain – Knowledge-Based Systems, 2020 – Elsevier
… When a chatbot is used by a business to answer users’ queries with a specific goal or focus on the completion of certain tasks requested by their customers, it is referred to as a service-based chatbot. Such chatbots are domain-specific and may use one of the above-mentioned …

Building a Chatbot: Architecture Models and Text Vectorization Methods
AV Chizhik, YA Zherebtsova – International Journal of Open Information …, 2020 – injoit.ru
… also discuss the issues of assessing the quality of chatbots response selection … language understanding, dialogue systems, intelligent chatbot, retrieval- based chatbot, word embeddings … UD parsing: Deep contextualized word embeddings, ensemble, and treebank concatenation …

A Mental Health Chatbot for Regulating Emotions (SERMO)-Concept and Usability Test
K Denecke, S Vaaheesan… – IEEE Transactions on …, 2020 – ieeexplore.ieee.org
… Analyzing emotions or sentiments resulting from inter- actions with chatbots has so far only rarely … On the one hand, the chatbot can be equipped with a personality and background … introduced a sentiment treebank that includes fine-grained sentiment labels to parse trees of …

A Survey on Modularization of Chatbot Conversational Systems
X Zhang, S He, Z Huang, A Zhang – International Conference on Database …, 2020 – Springer
… Researches relevant to the field of chatbot conversational systems have been developing … representation fusion network for multi-turn response selection in retrieval-based chatbots … Chuang, J.: Recursive deep models for semantic compositionality over a sentiment Treebank …

Language Model-Driven Chatbot for Business to Address Marketing and Selection of Products
AK Kushwaha, AK Kar – International Working Conference on Transfer and …, 2020 – Springer
… as more conversational data gets recorded by responding to customers through these hosted chatbots … J., Kubelka, J., Robbes, R., Bergel, A.: Building an Expert Recommender Chatbot … R., et al.: Recursive deep models for semantic compositionality over a sentiment treebank …

ClarQue: Chatbot Recognizing Ambiguity in the Conversation and Asking Clarifying Questions
SH Mody – 2020 – scholarsarchive.byu.edu
… 10 3.2 The Penn Treebank Project tags for parts of speech used by the Stanford POS tagger … 8 Page 18. Chapter 3 ClarQue: Chatbot That Deduces When and What Clarifying Questions to Ask Chatbots can reply in a variety of ways such as with a sentence, with an answer to …

Real-Time 2D Avatar Lip Syncing For The On Demand Interactive Chatbots
VS Lalam, A Dayal, SVR Sheik… – Recent Advances in …, 2020 – books.google.com
… gaming and the recent use in the education and the business domains for interactive chat-bots … Real-Time 2D Avatar Lip Syncing for the on Demand Interactive Chatbots in NLTK library … of corpus, like abc for plain-text corpora, brown for annotated corpora, treebank for parsed …

Design of Chatbot System for Student Counselling
SB Sonawane, AS Badwar, RH Dalvi, GN More… – ijniet.org
… For efficient counseling with the help of Chatbot we’ve a strong database that contains … Thus this is a student counseling chat bot, and user can get easy to choose desired … C. Potts, “Recursive deep models for semantic compositionality over a sentiment treebank,” in Proceedings …

Natural language processing In chatbot development: how does a chatbot process language?
A Heikkilä – 2020 – jyx.jyu.fi
… IN CHATBOT DEVELOPMENT: HOW DOES A CHAT- BOT PROCESS LANGUAGE … Heikkilä, Arttu Natural Language Processing In Chatbot Development: How Does a Chatbot Process Language … Chatbots are an extremely prominent way to interact with a software system …

Chatbot for food preferences modelling and recipe recommendation
ÁMFM Samagaio – 2020 – repositorio-aberto.up.pt
… 50 3.4 Nutrition and Health Related Chatbots … 126 6.2.4 Chatbot Usability Questionnaire . . . … 20 2.5 Named Entity Recognition example obtained using the StanfordNLP toolkit [80] 23 2.6 Penn Treebank Project [81] part-of-speech tagging [80] …

Topics for Projects
G Attardi – elearning.di.unipi.it
… Page 4. Chatbot • Alexa Topical Chat Dataset … Depling 2016 challenge requires tokenizer for any of the Universal Dependency TreeBank • Build a DL POS using CNN, for example a LSTM that uses word … http://2018.nliwod.org/challenge Page 13. Chatbots …

COVID-Twitter-BERT: A Natural Language Processing Model to Analyse COVID-19 Content on Twitter
M Müller, M Salathé, PE Kummervold – arXiv preprint arXiv:2005.07503, 2020 – arxiv.org
… This process generates a general language model that is then used as input for a supervised finetuning for specific language processing tasks, such as classification, question-answering models, and chatbots … 2.1.5 Stanford Sentiment Treebank 2 (SST-2) …

Natural language processing
RST Lee – Artificial Intelligence in Daily Life, 2020 – Springer
… and human voice synthesis also favors NLP-based AI applications development such as AI chatbots, customer service … Parse tree using TreeBank Corpus snapshot … application of natural language processing (NLP) is question-answering robots, or so-called chatbot (Raj 2018) …

Audrey: A Personalized Open-Domain Conversational Bot
CH Hong, Y Liang, SS Roy, A Jain, V Agarwal… – arXiv preprint arXiv …, 2020 – arxiv.org
… to the Alexa Prize Grand Challenge 3, Audrey, is an open-domain conversational chat-bot that aims to … the vision of naturally conversing artificial agents and built Audrey, an open domain chatbot that tackles all of the main challenges posed to open domain chatbots …

AD-CASPAR: Abductive-Deductive Cognitive Architecture based on Natural Language and First Order Logic Reasoning
CF Longo, C Santoro – researchgate.net
… Logic (FOL) Reasoning, as baseline platform for im- plementing scalable and flexible chatbots with both … word and POS is a Part-of-Speech tag from the Penn Treebank [10] tagset … text from a chatbot environment; the former allows a machine to understand the user’s speech and …

Rhetorical Structure Theory: A Comprehensive Review of Theory, Parsing Methods and Applications
S Hou, S Zhang, C Fei – Expert Systems with Applications, 2020 – Elsevier
… With an increasing number of research interests focus on RST, many novel parsing approaches have been proposed and motivated many brand new applications, such as chatbots and other expert and … Then the commonly used discourse treebank: RST-DT is elaborated …

Variable-Length Chromosome for Optimizing the Structure of Recurrent Neural Network
MH Aliefa, S Suyanto – … Conference on Data Science and Its …, 2020 – ieeexplore.ieee.org
… Once the optimum structure is found, then RNNLM will be trained using a full (100%) dataset. The optimum structured RNNMLs found by VLC-GA produce a perplexity of 57.46 on the Penn Treebank dataset … [9] YW Chandra and S. Suyanto, “Indonesian Chatbot of University …

An In-depth Walkthrough on Evolution of Neural Machine Translation
R Jagtap, D Dhage, N Sudhir – arXiv preprint arXiv:2004.04902, 2020 – arxiv.org
… The use cases of NMT models have been broadened from just language translations to conversational agents (chatbots), abstractive text summarization … This is called a LSTMN[6]. For sentiment analysis, Stanford Sentiment Treebank dataset was used where LSTMN got 87 …

Blind signal decomposition of various word embeddings based on join and individual variance explained
Y Wang, W Li – arXiv preprint arXiv:2011.14496, 2020 – arxiv.org
… We compared the performance of different decomposed components based on sentiment analysis on Twitter and Stanford sentiment treebank … One is Stanford Sentiment Treebank (Socher et al., 2013), the other is Twitter sentiment analysis dataset …

KIPoS@ EVALITA2020: Overview of the task on KIParla part of speech tagging
C Bosco, B Silvia, M Cerruti, E Goria… – EVALITA 2020 Seventh …, 2020 – iris.unito.it
… the experience of the Evalita 2016 PoSTWITA task on PoS tagging Ital- ian Social Media Texts (Bosco et al., 2016) and the subsequent development of an Italian treebank for social media … meaningfully used in the development of auto- matic conversation systems and chatbots …

NLP for the Greek Language: A Brief Survey
K Papantoniou, Y Tzitzikas – 11th Hellenic Conference on Artificial …, 2020 – dl.acm.org
… of the Greek Dependency Treebank11 with the Universal Dependen- cies v2 standard, and the extension of the treebank with enhanced … The thesis [38] describes a conversational chatbot system based on public services for a greek web portal called diadikasies.gr to help …

Advances in Computational Linguistics and Text Processing Frameworks
A Srivastav, H Khan, AK Mishra – Handbook of Research on …, 2020 – igi-global.com
… A brief description of chatbots and Memory Networks concludes the chapter … This thesis is concluded with the exploration of the advancing applications in the domain of Natural Language Processing like Chatbots and Memory Networks along with their architecture …

The Construction and Annotation of a Semantically Enriched Database: The Mandarin VerbNet and Its NLP Applications
M Liu – From Minimal Contrast to Meaning Construct, 2020 – Springer
… Although it avoids the problem of overgeneralisation of the semantic roles when compared with Sinica Treebank, it provides less information on verb classification and … For instance, in developing chatbots, it requires good semantic matching and identification of discourse acts …

Digital Marketing with Natural Language Processing
A Beg, N Tiwari – parishodhpu.com
… C. Chat bots … However, chatbots also help guide users through a customer journey to a sale … POS tagging The WSJ-PTB (the Wall Street Journal part of the Penn Treebank Dataset) corpus contains 1.17 million tokens and has been widely used for developing and evaluating POS …

A Panoramic Survey of Natural Language Processing in the Arab World
K Darwish, N Habash, M Abbas, H Al-Khalifa… – arXiv preprint arXiv …, 2020 – arxiv.org
… CamelParser is a dependency parser trained on CATiB treebank using MaltParser [134], a language-independent and data-driven dependency parser … Among the earliest research efforts on Arabic dialog applications is the Quran chatbot [168], where the conversation length is …

Modeling Machine Learning Agent for Interaction Conversational System Using Max Entropy Approach in Natural Language Processing
AK Negi, SI Hassan – Data Communication and Networks, 2020 – Springer
… In a service model which deliver the services like email, network, VPN, etc. There is a call center interface required where user come and interact with machine learning chatbot for registering his complaint … This tagging assigns to each word as per the Penn Treebank corpus …

Assessing Factoid Question-Answer Generation for Portuguese (Short Paper)
J Ferreira, R Rodrigues… – 9th Symposium on …, 2020 – drops.dagstuhl.de
… for creating question-answer pairs, structured as frequently asked questions (FAQ) lists, which can be useful for QA agents or chatbots … Both included models were trained in the Portuguese treebank Bosque 8.0 [6]. Resulting chunks are classified as nominal (NP), verbal (VP …

Natural language understanding in argumentative dialogue systems
PR Shigehalli – 2020 – oparu.uni-ulm.de
… In order to structure the user responses, we formalise the user interaction as an argument game. And we explore chat bot designs in order to understand the user intents in the game … In addition to VPAs, DS also find extensive applications in chatbots …

DREAM technical report for the Alexa Prize 2019
Y Kuratov, I Yusupov, D Baymurzina… – Alexa Prize …, 2020 – personeltest.ru
… In spite of the ubiquity of simple chatbots, the development of engaging conversational agents remains to be a big research and … A dataset of topic-oriented human-to-chatbot dialogues, 2018 … Recursive deep models for semantic compositionality over a sentiment treebank …

Processing of text using Artificial Neural Networks
V Balara, M Pošefko, M Rohácek – academia.edu
… In scope of what this work aims to study, the most widespread uses are e-commerce chatbots, translation engines and sign recognition in … In Stan- ford Sentiment Treebank (which role is predicting the sen- timent of movie reviews), there were few more classes to predict: very …

A Hybrid GCN and RNN Structure Based on Attention Mechanism for Text Classification
L Gao, J Wang, Z Pi, H Zhang, X Yang… – Journal of Physics …, 2020 – iopscience.iop.org
… Common machine translations, Chatbot and human-computer conversations are all the applications of natural language processing … This method has been tested on common datasets: bAbI, Stanford Sentiment Treebank and WSJ …

Noisy Text Data: Achilles’ Heel of BERT
A Srivastava, P Makhija, A Gupta – … of the Sixth Workshop on Noisy User …, 2020 – aclweb.org
… These include use cases such as chatbots, sentiment analysis systems, automatically routing and prioritizing customer support tickets, NER sys- tems … analysis we use popular datasets of IMDB movie reviews (Maas et al., 2011) and Stanford Sentiment Treebank (SST-2) (Socher …

A Review of Natural Language Processing Techniques for Sentiment Analysis using Pre-trained Models
L Mathew, VR Bindu – 2020 Fourth International Conference on …, 2020 – ieeexplore.ieee.org
… Experimental results based on Stanford Sentiment Treebank (SST) shows that the proposed method can increase conventional word … used multi-purpose model in NLP applications include machine translation, question answering systems, chatbots, sentiment analysis etc …

Generating Empathetic Responses by Looking Ahead the User’s Sentiment
J Shin, P Xu, A Madotto, P Fung – ICASSP 2020-2020 IEEE …, 2020 – ieeexplore.ieee.org
… Hence, it is natural to think that modeling empathy and eliciting it in chatbots are crucial towards bringing them even closer to … D. Manning, Andrew Ng, and Christopher Potts, “Recursive deep models for semantic composi- tionality over a sentiment treebank,” in Proceedings of …

Chinese Lexical Semantics: 20th Workshop, CLSW 2019, Beijing, China, June 28-30, 2019, Revised Selected Papers
JF Hong, Y Zhang, P Liu – 2020 – books.google.com
… 329 Yonghong Ke Page 13. xiv Contents “Love Is as Complex as Math”: Metaphor Generation System for Social Chatbot … 746 Xin Kou The Construction of Interactive Environment for Sentence Pattern Structure Based Treebank Annotation …

Experience grounds language
Y Bisk, A Holtzman, J Thomason, J Andreas… – arXiv preprint arXiv …, 2020 – arxiv.org
… From the beginning of corpus linguistics (Zipf, 1932; Har- ris, 1954), to the formation of the Penn Treebank (Marcus et al., 1993), NLP researchers have con- sistently recognized the limitations of corpora in terms of coverage of language and experience …

Open Korean Corpora: A Practical Report
WI Cho, S Moon, Y Song – arXiv preprint arXiv:2012.15621, 2020 – arxiv.org
… Among them, Korean occupies about 11K train pairs, and 1,698/1,722 for dev/test each. XPersona [inter, com, rd] Lin et al. (2020) is a dataset for evaluating personalized chatbots44. It provides the dataset of Zhang et al. (2018 …

THE RUSSIAN LANGUAGE PIPELINE IN THE LIMA MULTILINGUAL ANALYZER
B VV, G de Chalendar – dialog-21.ru
… A new version of Universal Dependencies treebank collection is released twice a year. Current version UD 2.5 includes 157 treebanks for 90 languages … DeepPavlov is an open source framework for chatbots and virtual assistants de- velopment …

User Generated Data: Achilles’ Heel of BERT
A Kumar, P Makhija, A Gupta – arXiv preprint arXiv:2003.12932, 2020 – arxiv.org
… case, it is applicable across various use cases in industry – be it be sentiment classification on twitter data or a mobile based chat bot … We work with three datasets namely – IMDB movie reviews[8], Stanford Sentiment Treebank (SST-2) [9] and Semantic Textual Similarity (STS-B …

Anaphora Resolution in Chinese for Analysis of Medical Q&A Platforms
A Tsvetkova – CCF International Conference on Natural Language …, 2020 – Springer
… There are a number of corpora with annotated coreference links such as OntoNotes, Chinese ACE 2004 and Chinese ACE 2005, Penn Chinese Treebank … Wolf, T.: State-of-the-art neural coreference resolution for chatbots …

TexSmart: A Text Understanding System for Fine-Grained NER and Enhanced Semantic Analysis
H Zhang, L Liu, H Jiang, Y Li, E Zhao, K Xu… – arXiv preprint arXiv …, 2020 – arxiv.org
… For example, when a chatbot is processing query “please book an air ticket to London at 4 pm the day after tomorrow”, it … with a precise date in JSON format: {“value”: [2019, 2]}. Deep semantic representation is important for applications like task-oriented chatbots, where the …

A framework for applying natural language processing in digital health interventions
B Funk, S Sadeh-Sharvit, EE Fitzsimmons-Craft… – Journal of medical …, 2020 – jmir.org
… eg, a change in target symptoms) [9]. If proven effective, NLP models may ultimately enable the design of automated chatbots in person … For generating POS features, we used the Apache OpenNLP library that categorizes words according to the Penn Treebank tag set [32] …

NATURAL LANGUAGE PROCESSING IN ARTIFICIAL INTELLIGENCE: A FUNCTIONAL LINGUISTIC PERSPECTIVE
K Panesar – The Age of Artificial Intelligence: An Exploration, 2020 – books.google.com
… and Mott 2004), which include: (1) development of large corpora of tagged text, for instance, the Brown Corpus, the Penn Treebank and the … net”, 2015) as in the Chatbot ‘Mitzuki’in 2013, 2016, 2017 and 2018, built on Pandorabots: the world’s leading conversational (AI) Chatbot …

Data Extraction and Preprocessing for Automated Question Answering Based on Knowledge Graphs
A Romanov, D Volchek, D Mouromtsev – World Conference on Information …, 2020 – Springer
… Depending on the application context, such systems are called a dialog interface, question-answering system, or chatbot … 1. Dale, R.: The return of the chatbots. Nat … R., Petrov, S., Pyysalo, S., Silveira, N., Tsarfaty, R.: Universal dependencies v1: a multilingual treebank …

A reactive cognitive architecture based on natural language processing for the task of decision-making using a rich semantic
CF Longoa, F Longob, C Santoroa – Session 5: Agents & Actors for …, 2020 – cris.unibo.it
… label is in the form L: POS (t), where L is a lemmatized word and POS is a Part-of-Speech (POS) tag from the Penn Treebank tagset [16]. 204 … [5] R. Kar, R. Haldar, Applying Chatbots to the … [6] CJ Baby, FA Khan, JN Swathi, Home automation using IoT and a chatbot using natural …

A comprehensive review on feature set used for anaphora resolution
K Lata, P Singh, K Dutta – Artificial Intelligence Review, 2020 – Springer
In linguistics, the Anaphora Resolution (AR) is the method of identifying the antecedent for anaphora. In simple terms, this is the problem that helps to s.

Unsupervised Paraphrase Generation using Pre-trained Language Models
C Hegde, S Patil – arXiv preprint arXiv:2006.05477, 2020 – arxiv.org
… [26] Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, Andrew Ng, and Christopher Potts. Recursive deep models for semantic compositionality over a sentiment treebank … Lingke: a fine-grained multi-turn chatbot for customer service …

Attention-based hierarchical recurrent neural networks for MOOC forum posts analysis
N Capuano, S Caballé, J Conesa, A Greco – Journal of Ambient …, 2020 – Springer
… A research field which can greatly benefit from the analysis of forum posts in MOOCs settings is the area of pedagogical conversational agents (aka, chatbots), which have been designed and successfully developed to support effective interaction and learning in these settings …

Gunrock 2.0: A user adaptive social conversational system
K Liang, A Chau, Y Li, X Lu, D Yu, M Zhou… – arXiv preprint arXiv …, 2020 – arxiv.org
… Test. In comparison, social chatbots require more in-depth communication skills with emotional support[27]. Gunrock … conversations. For comparison, in 2018, our chatbot Gunrock reached 3.62 across all conversations. Gunrock …

The state of the art of deep learning models in medical science and their challenges
C Bhatt, I Kumar, V Vijayakumar, KU Singh… – Multimedia Systems, 2020 – Springer
… However, various attempts made by different groups have enabled the possibilities of implementing such simulation that has led to the development of a variety of concepts like a virtual assistant (Alexa, Siri, Cortana), language translation Chatbot, Image colorization, facial …

TV-AfD: An Imperative-Annotated Corpus from The Big Bang Theory and Wikipedia’s Articles for Deletion Discussions
Y Xiao, ZY Slaton, L Xiao – … of The 12th Language Resources and …, 2020 – aclweb.org
… environment. Sometimes, people interact with chatbots online to make inquiries and requests or try to find instructional information from online discussions and resources … instances. The English Web Treebank (Ann Bies et al …

COVID-19 Pandemic: Identifying Key Issues using Social Media and Natural Language Processing
O Oyebode, C Ndulue, D Mulchandani… – arXiv preprint arXiv …, 2020 – arxiv.org
… The regular grammar above is composed of patterns of POS tags from the well-established Penn Treebank Tagset [52], [53] … Page 4. 3) POS Tagging Each token is assigned a POS tag (within the Penn Treebank Tagset) denoting its part of speech in the English language …

The Role of KM in Enhancing AI Algorithms and Systems
H AlGhanem, M Shanaa, S Salloum… – Advances in Science …, 2020 – academia.edu
… P9 [56] Knowledge Application /Decision making Chatbot Case Study General … to Table 4, it seems that knowledge application and decision-making processes have a positive impact on Neural Networks, including ANN, RNN, and CNN [31], Decision Trees [33], and Chatbots [56 …

IEC: Towards Interest-Eliciting Neural Conversational Agents
Z Yao, Y Zhang, X Li, J Gao, M Galley, C Brockett… – ziyuyao.org
… Tang et al.; Wu et al.; Qin et al. (2019; 2019; 2020) also explored goal-driven open-domain chat- bots, but their goals are specified keywords or entities in a Page 3 … The data statis- tics are shown in Table 2. Each utterance was Treebank- tokenized and lowercased …

WellBe: A Conversational Agent for Well-Being
J Wu – 2020 – escholarship.org
… tains dialogues related to 32 emotions. However chatbots based on this corpus are still at an early stage of development … generation as we discuss in more detail in the remainder of this thesis. Another approach is exemplified by the empathetic social chatbot Microsoft …

Understanding EFL Linguistic Models through Relationship between Natural Language Processing and Artificial Intelligence Applications
M Salim Keezhatta – Arab World English Journal (AWEJ) Volume, 2020 – papers.ssrn.com
… These models relate to machine translation, question answering systems, chatbots, sentiment analysis and other core issues of language modeling … Recursive deep models for semantic compositionality over a sentiment treebank …

Plug-and-play conversational models
A Madotto, E Ishii, Z Lin, S Dathathri, P Fung – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. Plug-and-Play Conversational Models Andrea Madotto1?, Etsuko Ishii?1, Zhaojiang Lin?1, Sumanth Dathathri?†, Pascale Fung1 1The Hong Kong University of Science and Technology {amadotto,eishii,zlinao,pascale}@ust.hk sdathath@gmail.com Abstract …

Do Neural Models for Response Generation Fully Exploit the Input Natural Language Text?
L ZHANG, T SAKAI – db-event.jpn.org
… Key words Seq2seq Model, Chat Bot, Natural Language Processing 1 Introduction … [9] trained an LSTM-based language model on Penn Treebank [11] and Wikitext- 2 [12] datasets to make prediction on the next word after one se- quence …

A deep learning analysis on question classification task using Word2vec representations
S Yilmaz, S Toklu – Neural Computing and Applications, 2020 – Springer
… This chatbot are able to response to the users, but messages produced by the chatbot should be enhanced to obtain a meaningful dialogue by enlarging the dataset … English Penn treebank using an additional treebank with 1153 words Lexical feature, POS tags …

Health, Psychosocial, and Social issues emanating from COVID-19 pandemic based on Social Media Comments using Natural Language Processing
O Oyebode, C Ndulue, A Adib, D Mulchandani… – arXiv preprint arXiv …, 2020 – arxiv.org
… 61]. Part-of-Speech (PoS) Tagging The tagging module associates each token with its part of speech. The part of speech tags are based on the Penn Treebank tagset [58,62], some of which are shown in Table 1. Page 9. Lemmatization …

Knowledge-guided unsupervised rhetorical parsing for text summarization
S Hou, R Lu – Information Systems, 2020 – Elsevier
… We first proposed an unsupervised Chinese-oriented rhetorical parsing method. Existing rhetorical parsing methods are English-oriented, supervised methods that often trained on RST-DT, a human-annotated discourse treebank of WSJ articles under the framework of RST …

AI-driven IT and its Potentials–a State-of-the-Art Approach
M Glintschert – Available at SSRN 3576417, 2020 – papers.ssrn.com
… Within the CoreNLP, the functionality of sentiment analysis has been enhanced by a Sentiment Treebank and Recursive Neural Tensor Network (Socher et al., 2013). Electronic copy available at: https://ssrn.com/abstract=3576417 Page 20. 17 …

A Neural Network Based Hybrid Model for Depression Detection in Twitter
B Verma, S Gupta, L Goel – … Conference on Advances in Computing and …, 2020 – Springer
… The Stanford Sentiment Treebank (SST) benchmark [43] dataset is used and CNN extracts feature through the convolution matrix & fed it to LSTM to learn features for long … Some applications of RNN are; Chatbots, machine translation, image categorization, and text classification …

Data query language and corpus tools for slot-filling and intent classification data
S Larson, E Guldan, K Leach – … of The 12th Language Resources and …, 2020 – aclweb.org
… Keywords: corpus, conversational systems/dialogue/chatbots/human-robot interaction, tools … WebApplications (Braun et al., 2017) 89 8 3 294 0.658 0.949 — Chatbot (Braun et al., 2017) 206 2 7 184 0.134 0.837 — Liu et al. (2019) 25,716 68 56 7,955 0.178 0.948 — Larson et al …

Template-based Question Answering using Recursive Neural Networks
RG Athreya, S Bansal, AC Ngonga-Ngomo… – arXiv preprint arXiv …, 2020 – arxiv.org
… The tagger uses the Penn Treebank Tagset [21] for tagging the individual parts of speech and the Java implementation (v3.9.1) of the tagger was used. For example, consider the question “Philadelphia City Council is the governing body of which city ?” …

AraBERT: Transformer-based model for Arabic language understanding
W Antoun, F Baly, H Hajj – arXiv preprint arXiv:2003.00104, 2020 – arxiv.org
… Towards a human-like open-domain chatbot. Al Sallab, A., Hajj, H., Badaro, G., Baly, R., El-Hajj, W., and Shaban, K. (2015) … A sentiment treebank and morphologically enriched recursive deep models for effective sentiment analysis in arabic …

Tools and Methodology for Converting Natural Language into RDF Representations
O Loia, E Kamateri, PD Vasileiadis – academia.edu
… by predicting a sequence of transitions until it approaches the final configuration, these transitions are learned from gold sequences of transitions in a treebank, which are … 3.7 LUIS The advance of conversational chatbots increased the need for natural language understanding …

Customizing Triggers with Concealed Data Poisoning
E Wallace, TZ Zhao, S Feng, S Singh – arXiv preprint arXiv:2010.12563, 2020 – arxiv.org
… unsophisticated data poisoning attacks have even been deployed on Gmail’s spam filter (Bursztein, 2018) and Microsoft’s Tay chatbot (Lee, 2016) … Dataset and Model We use the binary Stanford Sentiment Treebank (Socher et al., 2013, SST-2) using the GLUE splits (Wang et al …

Automatic Classification of Text Complexity
V Santucci, F Santarelli, L Forti, S Spina – Applied Sciences, 2020 – mdpi.com
… world applications such as, just to name a few: automatic translation [4], text summarization [5], speech recognition [6], chatbots and virtual … Therefore, their accuracy is highly dependent on the treebank corpus—as it is usually called, a manually annotated text corpus—adopted …

Natural language processing (NLP) in Artificial Intelligence (AI): a functional linguistic perspective
K Panesar – 2020 – bradscholars.brad.ac.uk
… Branting, and Mott 2004), which include: (1) development of large corpora of tagged text, for instance, the Brown Corpus, the Penn Treebank and the British National … in the Chatbot ‘Mitzuki’ in 2013, 2016, 2017 and 2018, built on Pandorabots: the …

The recipes of Philosophy of Science: Characterizing the semantic structure of corpora by means of topic associative rules
C Malaterre, JF Chartier, F Lareau – Plos one, 2020 – journals.plos.org
… Lemmatization and tagging were done using the TreeTagger algorithm [8] together with Penn TreeBank for tagging [9]. Because not all types of words are proper candidates for expressing topics and may introduce noise (for instance: determinants, prepositions or pronouns …

Detection of acute 3, 4-methylenedioxymethamphetamine (MDMA) effects across protocols using automated natural language processing
C Agurto, GA Cecchi, R Norel, R Ostrand… – …, 2020 – ncbi.nlm.nih.gov
… These methods are routinely used in industry for the purpose of speech recognition [5], chatbots and conversation agents [6], and recommender systems [7] among others … Using the Treebank tagger in NTLK, we parsed interviews into sentences and identified nouns …

Comparing Different Methods for Assigning Portuguese Proverbs to News Headlines
R Mendes, HG Oliveira – Procs. of 11th ICCC, ICCC, 2020 – computationalcreativity.net
… Furthermore, in the domain of chatbots, using proverbs and sayings in the appro- priate contexts could make conversations more interesting … Afterwards, the authors were able to classify the relations between words based on a dependency treebank, and select the keywords …

SqueezeBERT: What can computer vision teach NLP about efficient neural networks?
FN Iandola, AE Shaw, R Krishna… – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. arXiv:2006.11316v1 [cs.CL] 19 Jun 2020 SqueezeBERT: What can computer vision teach NLP about efficient neural networks? Forrest N. Iandola forresti@berkeley.edu Albert E. Shaw ashaw596@gmail.com Ravi Krishna UC Berkeley EECS ravi.krishna@berkeley.edu …

Proxy Indicators for the Quality of Knowledge-grounded Dialogues
R Nedelchev, J Lehmann, R Usbeck – 2020 – openreview.net
… grammatically sound a conversation is. Stanford Sentiment Treebank (SST-2) [27] contains text excerpts from the movie reviews that have their sentiments annotated by humans as positive (one) or as negative (zero). While it is not …

Summarized Logical Forms Based on Abstract Meaning Representation and Discourse Trees
B Galitsky – Artificial Intelligence for Customer Relationship …, 2020 – Springer
… In some cases, autonomous agents (chatbots) can import such question–answer pairs in order to answer user questions … Therefore, for a CRM chatbot or a search engine it is still hard to rely on available statistical-based or machine learning-based relevance to yield a high …

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings
T Cohn, Y He, Y Liu – Proceedings of the 2020 Conference on Empirical …, 2020 – aclweb.org
… 1307 Parsing with Multilingual BERT, a Small Treebank, and a Small Corpus Ethan C. Chau, Lucy H. Lin and Noah A. Smith … Filtering before Iteratively Referring for Knowledge-Grounded Response Selection in Retrieval-Based Chatbots Jia-Chen Gu, Zhenhua Ling, Quan Liu …

Adversarial Black-Box Attacks On Text Classifiers Using Multi-Objective Genetic Optimization Guided By Deep Networks
A Mathai, S Khare, S Tamilselvam, S Mani – arXiv preprint arXiv …, 2020 – arxiv.org
… 1 Introduction Deep Neural Networks (DNNs) have witnessed tremendous success in day to day applications like chat-bots and self-driving vehicles … Stanford Sentiment Treebank (SST-2) (Socher et al., 2013) and IMDB movie reviews (Maas et al., 2011) …

The Impact of Romanian Diacritics on Intent Detection and Slot Filling
AD Stoica, AC Rad, IH Muntean… – … , Quality and Testing …, 2020 – ieeexplore.ieee.org
… 159–161. [6] “IBM Watson.” [Online]. Available: https://www.ibm.com/watson [7] “Rasa,” Rasa NLU: Language Understanding for Chatbots and AI assistants … [13] V. Barbu Mititelu, R. Ion, R. Simionescu, E. Irimia, and C.-A. Perez, “The romanian treebank annotated according to …

Automatic Poetry Classification and Chronological Semantic Analysis
A Rahgozar – 2020 – ruor.uottawa.ca
… An important aspect of NLP is how data is presented to the computer, and much work was done in the 1970s in this area (O’Connor, 2012). For example, chatbot research found that enabling a computer to carry on a conversation and to imitate human dialogue is a difficult task …

A Deep Learning System for Sentiment Analysis of Service Calls
Y Jia, S SungChu – arXiv preprint arXiv:2004.10320, 2020 – arxiv.org
… However, with the advent of Human-Robot Interaction (HRI) such as voice as- sistants and customer service chatbots, researchers have started to build empathetic dialogue systems to improve the overall HRI experience by adapting to customers’ sentiment …

Proceedings of The 12th Language Resources and Evaluation Conference
N Calzolari, F Bechet, P Blache, K Choukri… – Proceedings of The …, 2020 – aclweb.org
Page 1. LREC 2020 Marseille TWELFTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION May 11-16 , 2020 PALAIS DU PHARO Marseille, France CONFERENCE PROCEEDINGS Editors …

Understanding and generating language with abstract meaning representation
M Damonte – 2020 – era.ed.ac.uk
… inference component (for example, a dialogue manager in dialogue systems and chatbots), which can reason over the meaning representation. The output … opment of a public corpus of sentences annotated with syntactic trees: the Penn Treebank (Marcus et al., 1993) …

Syntax-aware opinion role labeling with dependency graph convolutional networks
B Zhang, Y Zhang, R Wang, Z Li, M Zhang – Proceedings of the 58th …, 2020 – aclweb.org
… Dependency Parser. Following the standard practice in the dependency parsing community, the original phrase-structure Penn Treebank data are converted into the Stanford dependencies using the Stanford Parser v3.3.0 …

AraBERT: Transformer-based Model for Arabic Language Understanding
F Baly, H Hajj – Proceedings of the 4th Workshop on Open-Source …, 2020 – aclweb.org
… Towards a human-like open-domain chatbot. Al Sallab, A., Hajj, H., Badaro, G., Baly, R., El-Hajj, W., and Shaban, K. (2015) … A sentiment treebank and morphologically enriched recursive deep models for effective sentiment analysis in arabic …

Detection of Acute 3, 4-Methylenedioxymethamphetamine (MDMA) Effects Across Protocols Using Automated Natural Language Processing
MJB Kirkpatrick, MC Wardle, H de Wit – nature.com
… These methods are routinely used in industry for the purpose of speech recognition [5], chatbots and conversation agents [6], and recommender systems [7] among others … Toolkit (NLTK; [30]). Using the Treebank tagger in NTLK, we parsed interviews into …

Tackling the Long Tail in Language Understanding
A Naik – 2020 – cs.cmu.edu
… Subsequent years saw the development of ELIZA (Weizenbaum, 1966), a rule-based chatbot that could carry out conversations on many topics … using benchmark datasets for model development and evaluation, dat- ing back to the creation of the Penn Treebank dataset (Marcus …

Evaluating machines by their real-world language use
R Zellers, A Holtzman, E Clark, L Qin, A Farhadi… – arXiv preprint arXiv …, 2020 – arxiv.org
… capture historic patterns of language. For instance, in our field, we commonly evaluate syntactic understand- ing using the Penn Treebank dataset, which con- tains news articles from 1989 (Marcus et al., 1993). However, the …

Efficient Urdu Caption Generation using Attention based LSTMs
I Ilahi, HMA Zia, A Ehsan, R Tabassam… – arXiv preprint arXiv …, 2020 – arxiv.org
… 1*** This is a project report for the Deep Learning Course (Spring 2020) being taught at Information Technology University, Lahore, Pak- istan *** automated chat-bots in native languages … A multi-representational and multi- layered treebank for hindi/urdu …

Neighborhood-based Pooling for Population-level Label Distribution Learning
TC Weerasooriya, T Liu, CM Homan – arXiv preprint arXiv:2003.07406, 2020 – arxiv.org
Page 1. Neighborhood-based Pooling for Population-level Label Distribution Learning Tharindu Cyril Weerasooriya1 and Tong Liu2 and Christopher M. Homan3 Abstract. Supervised machine learning often requires human- annotated data …

Computational models of coherence for open-domain dialogue
A Cervone – Computer Science, 2020 – iris.unitn.it
Page 1. DEPARTMENT OF INFORMATION ENGINEERING AND COMPUTER SCIENCE ICT International Doctoral School DOCTORAL THESIS Computational models of coherence for open-domain dialogue …

Facilitating Corpus Usage: Making Icelandic Corpora More Accessible for Researchers and Language Users
S Steingrímsson, S Barkarson… – Proceedings of The 12th …, 2020 – aclweb.org
… build- ing chatbots. But such information is also important when building study material for the language classroom (see eg Gabrialatos, 2005) … Recursive deep models for semantic compositionality over a sentiment treebank. In …

A Vietnamese Dataset for Evaluating Machine Reading Comprehension
K Van Nguyen, DV Nguyen, AGT Nguyen… – arXiv preprint arXiv …, 2020 – arxiv.org
… MRC is an important core for a range of NLP applications such as question answering, next-generation search engines, intelligent agents (Alexa, Google Assistant, Siri, and Cortana), chatbots and robots … Ensuring annotation consistency and accuracy for vietnamese treebank …

Asymmetric Attributional Word Similarity Measures to Detect the Relations of Textual Generality
S Pais, G Dias – Computers, 2020 – mdpi.com
… For instance, it has been applied in text summarization [3,4], machine translation [5], and more recently, the concept of chatbots [6,7]. Given the multiple applications that textual entailment can have, we understand that there are several types of implications, where each type of …

An Evaluation of Automatic Test Case Generation strategy from Requirements for Electric/Autonomous Vehicles
A Gangadharan – 2020 – diva-portal.org
… NLP has several popular applications such as speech recognition, language translation, spell-checking, finding plagiarism, and chatbots … Few of the NLP techniques used in this generation process are POS Tagging, Treebank, WordNet8, Measuring similarity, Lemmatization & …

Applied natural language processing inspired by fundamental mathematics and physics
RR Dangovski – 2020 – dspace.mit.edu
… part-of-speech tagging and named entity recognition to neural machine translation, text summarization, question answering, and building chatbots/dialog systems … modeling on the Penn Treebank; 5. Perform effective seq2seq text summarization …

Countering language drift with seeded iterated learning
Y Lu, S Singhal, F Strub, A Courville… – … on Machine Learning, 2020 – proceedings.mlr.press
Page 1. Countering Language Drift with Seeded Iterated Learning Yuchen Lu 1 Soumye Singhal 1 Florian Strub 2 Olivier Pietquin 3 Aaron Courville 1 4 Abstract Pretraining on human corpus and then finetuning in a simulator …

KLPT–Kurdish Language Processing Toolkit
S Ahmadi – Proceedings of Second Workshop for NLP Open …, 2020 – aclweb.org
Page 1. Proceedings of Second Workshop for NLP Open Source Software (NLP-OSS), pages 72–84 Virtual Conference, November 19, 2020. c 2020 Association for Computational Linguistics 72 KLPT – Kurdish Language Processing Toolkit …

Beneath the Tip of the Iceberg: Current Challenges and New Directions in Sentiment Analysis Research
S Poria, D Hazarika, N Majumder… – arXiv preprint arXiv …, 2020 – arxiv.org
… phrases. This work also proposed the Stanford Sentiment Treebank corpus comprising of parse trees fully labeled with sentiment labels … Section 2.3 presents one such example where a user is chatting with a chit-chat style chatbot. In …

Combinatory Categorial Grammar for Hebrew
E Agami – 2020 – idc.ac.il
… Modern parsers use machine learning (ML) to help predict the most likely interpre- tation. Training these algorithms requires a treebank annotated according to the SRT (cor- pus) … Example use cases are querying dataset or executing command (chat bots) in natural language …

A Companion Robot for Modeling the Expressive Behavior of Persons with Parkinson’s Disease
AP Valenti – 2020 – search.proquest.com
Page 1. A Companion Robot for Modeling the Expressive Behavior of Persons with Parkinson’s Disease A dissertation submitted by Andrew P. Valenti, BS, MS, New York University In partial fulfillment of the requirements for the degree of Doctor of Philosophy in …

The Comparison Between the Tools for Named Entity Recognition
W Zhang – 2020 – openrepository.aut.ac.nz
… can even “talk” with our electronic devices (chatbots). In erstwhile times, researchers … 1]: Machine translation, extraction of critical information, summarization of literature, chatbot, medical analysis, detection of spam emails. Page 13. 4 This …

Learning meaning representations for text generation with deep generative models
K Cao – 2020 – repository.cam.ac.uk
… canonicalisation of the pronoun myself to the concept I. . . . . 113 5.3 An example Penn treebank-style constituency tree for an example sentence … On the other end of the spectrum, the Penn Treebank (Marcus et al., 1993) used 15 graduate linguistics students …

Structure-Level Knowledge Distillation For Multilingual Sequence Labeling
X Wang, Y Jiang, N Bach, T Wang, F Huang… – arXiv preprint arXiv …, 2020 – arxiv.org
… Many tasks such as named entity recognition (NER) and part-of-speech (POS) tagging can be formulated as sequence labeling problems and these tasks can provide extra informa- tion to many downstream tasks and products such as searching engine, chat-bot and syntax …

Customizable text generation via conditional text generative adversarial network
J Chen, Y Wu, C Jia, H Zheng, G Huang – Neurocomputing, 2020 – Elsevier
JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …

Profile Consistency Identification for Open-domain Dialogue Agents
H Song, Y Wang, WN Zhang, Z Zhao, T Liu… – arXiv preprint arXiv …, 2020 – arxiv.org
… In contrast, there is no universal dependency structure in the responses. To obtain the structures in the responses, we trained a parser on CDT5.0 (Chineses dependency treebank), achieving 90.72% and 88.38% unlabeled and la- beled attachment score …

Natural Language Processing Advancements By Deep Learning: A Survey
A Torfi, RA Shirvani, Y Keneshloo, N Tavvaf… – arXiv preprint arXiv …, 2020 – arxiv.org
… Another type of parsing is called Dependency Parsing. De- pendency structure shows the structural relationships between the words in a targeted sentence. In dependency parsing, 7Penn Treebank Wall Street Journal (WSJ-PTB). 8Conditional Random Field. Page 8 …

Building A User-Centric and Content-Driven Socialbot
H Fang – arXiv preprint arXiv:2005.02623, 2020 – arxiv.org
… bots in the literature have adopted approaches different from task-oriented systems including … based chatbots, including speech recognition errors, lack of sentence segmentation, disfluencies … two popular approaches used for chatbot systems, ie, scripting responses with template …

Robotics at workplace: An integrated Twitter analytics–SEM based approach for behavioral intention to accept
N Sinha, P Singh, M Gupta, P Singh – International Journal of Information …, 2020 – Elsevier

A Pilot Study on Multiple Choice Machine Reading Comprehension for Vietnamese Texts
K Van Nguyen, KV Tran, ST Luu, AGT Nguyen… – arXiv preprint arXiv …, 2020 – arxiv.org
… MRC. Findings of this research field are implemented into various artificial intelli- gence applications such as next-generation search engines, intelligent agents (Alexa, Google Assistant, Siri, Cortana, etc), chatbots and robots …

The Art of Natural Language Processing: Classical, Modern and Contemporary Approaches to Text Document Classification
A Ferrario, M Naegelin – … to Text Document Classification (March 1 …, 2020 – papers.ssrn.com
… like policy contracts or claims notifications, as well as the possibility of recording customers’ interactions with corporate con- versational assistants (‘chatbots’), provide data … The tokenizer uses the original Treebank11 tokenizer, which tok- enizes text using regular expressions …

Opportunities, Tools, and New Insights: Evidence on Emotions in Service from Analyses of Digital Traces Data
A Rafaeli, GBY Tov, S Ashtar, D Altman – Emotions and Service in the …, 2020 – emerald.com
… (2016) analyzed Twitter interactions to identify specific emotions (eg, anger, frustration) in service conversations of employees and customers. In this vein, Hu et al. (2018) describe creation of a tone-aware chatbot for interactions with customer requests on social media …

Biomedical Text Dependency Parsing with the Neural Turku Parser
T Ngo Minh – 2020 – doria.fi
… For most of the history of NLP, phrase structure grammar was the more popular ap- proach with a large proportion of work specifically on the Penn Treebank (Marcus et al., 1993) … treebank, an indispensable component of contemporary parsing, was not widely used …

Cortex: A Compiler for Recursive Deep Learning Models
P Fegade, T Chen, P Gibbons, T Mowry – arXiv preprint arXiv:2011.01383, 2020 – arxiv.org
… 1 INTRODUCTION Deep learning models are increasingly being used in produc- tion as part of applications such as personal assistants, self- driving cars (Maqueda et al., 2018; Bojarski et al., 2016) and chatbots (Yan et al., 2016; Li et al., 2016) …

Efficient algorithms and hardware for Natural Language Processing
H Wang – 2020 – dspace.mit.edu
… applications, including machine translation, document summarization, and chatbots. With the rise of Deep Learning (DL) [48], Neural Network (NN) models were widely … Senti- ment classification such as Stanford Sentiment Treebank V2 (SST-2) [80] is a typical …

Learning to represent healthcare providers knowledge of neonatal emergency care: findings from a smartphone-based learning intervention targeting clinicians from …
T Tuti, C Paton, N Winters – … of the Tenth International Conference on …, 2020 – dl.acm.org
Page 1. Learning to Represent Healthcare Providers Knowledge of Neonatal Emergency Care Findings From A Smartphone-Based Learning Intervention Targeting Clinicians From LMICs Timothy Tuti† Learning and New Technologies …

AI Undercover Agents: A Machine Learning Solution to Online Pedophilia
B Cantwell – 2020 – search.proquest.com
… Page 20. 14 level information to classify texts coming from two different datasets: the Stanford Sentiment Treebank, containing short movie reviews, and the Stanford Twitter Sentiment corpus. The model achieved respective accuracies of 0.857 and 0.864 [22] …

Learning to represent healthcare providers knowledge of neonatal emergency care
C Paton, N Winters, T Tuti – … of the Tenth International Conference on …, 2020 – ora.ox.ac.uk
… such anomalous learning behaviour. Such gamification learning modes can be linked to a human instructor, professional colleagues, or even chatbots to help guide this elaborative way of learning. Future research should consider …

New vietnamese corpus for machine readingcomprehension of health news articles
K Van Nguyen, DV Nguyen, AGT Nguyen… – arXiv preprint arXiv …, 2020 – arxiv.org
… language. In addition, machine comprehension for health domain has few studies so far, although it could be implemented into various potential for practical appli- cations such as chatbot and virtual assistant in health-care service …

Variational Inference for Text Generation: Improving the Posterior
V Balasubramanian – 2020 – uwspace.uwaterloo.ca
… Some of the applications and research sub-fields of NLG have attracted recent research interest with the success of deep learning for text, they include, but are not limited to: • Dialogue Response Generation: This task is quite common in chatbots and other similar services …

Enhancing lexical-based approach with external knowledge for Vietnamese multiple-choice reading comprehension
K Van Nguyena, KV Trana, ST Luua… – arXiv preprint arXiv …, 2020 – academia.edu
… of MRC. Findings of this research field are implemented into various artificial intelligence applications such as next-generation search engines, AI agents (Alexa, Google Assistant, Siri, Cortana, etc.), chatbots, and robots. One …

Countering Language Drift with Neural Iterated Learning
Y Lu, S Singhal, F Strub, O Pietquin, A Courville – 2020 – research.google
Page 1. Countering Language Drift with Seeded Iterated Learning Yuchen Lu 1 Soumye Singhal 1 Florian Strub 2 Olivier Pietquin 3 Aaron Courville 1 4 Abstract Pretraining on human corpus and then finetuning in a simulator …

Joint Word Segmentation and Part-of-Speech Tagging for Myanmar Language
DL Cing, KM Soe – 2020 – onlineresource.ucsy.edu.mm
Page 1. JOINT WORD SEGMENTATION AND PART-OF- SPEECH TAGGING FOR MYANMAR LANGUAGE DIM LAM CING UNIVERSITY OF COMPUTER STUDIES, YANGON August, 2020 Page 2. Joint Word Segmentation and Part-of-Speech Tagging for Myanmar Language …

Language (Technology) is Power: A Critical Survey of” Bias” in NLP
SL Blodgett, S Barocas, H Daumé III… – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. arXiv:2005.14050v1 [cs.CL] 28 May 2020 Language (Technology) is Power: A Critical Survey of “Bias” in NLP Su Lin Blodgett College of Information and Computer Sciences University of Massachusetts Amherst blodgett@cs.umass.edu …

STYLIZED NATURAL LANGUAGE GENERATION IN DIALOGUE SYSTEMS
K BOLSHAKOVA – dspace.vutbr.cz
… topics). To escape from the limitation, recent interest of research started moving to non-task-oriented chitchat dialogues (chatbots). Chitchat … etc. Chatbots have also been used for testing theories of psychological counseling [53]. The …

Learning to Represent Healthcare Providers Knowledge of Neonatal Emergency Care
T Tuti, C Paton, N Winters – researchgate.net
Page 1. Learning to Represent Healthcare Providers Knowledge of Neonatal Emergency Care Findings From A Smartphone-Based Learning Intervention Targeting Clinicians From LMICs Timothy Tuti† Learning and New Technologies …

Dissecting Fact-Checking Systems: The Impact of Evidence Extraction Methods
PJL Azevedo – 2020 – repositorio-aberto.up.pt
… 2.1 Tags proposed in the Penn Treebank [71] … Many applications are already based on NLP, for example, to make a summary of a text [34], the construction of generic or domain-specific chatbots, structuring of argumentative texts [92], question answering, among many other …

Deep learning for drug–drug interaction extraction from the literature: a review
T Zhang, J Leng, Y Liu – Briefings in bioinformatics, 2020 – academic.oup.com
Abstract. Drug–drug interactions (DDIs) are crucial for drug research and pharmacovigilance. These interactions may cause adverse drug effects that threaten pub.

Automatic voice emotion recognition of child-parent conversations in natural settings
ELC Law, S Soleimani, D Watkins… – Behaviour & Information …, 2020 – Taylor & Francis
ABSTRACTWhile voice communication of emotion has been researched for decades, the accuracy of automatic voice emotion recognition (AVER) is yet to improve. In particular, the intergenerational comm…

Predicting the Pandemic: Sentiment Evaluation and Predictive Analysis of Large-Scale Tweets on Covid-19 by Deep Convolutional Neural Network
S Das, AK Kolya – researchgate.net
… grams. These sets of features could then be used for specialized tasks such as sentiment analysis, text summarization, automatic encoding or decoding, machine translation, and question answering (QA) via digital chatbots [30] …

Transformer-Based Observers in Psychotherapy
T Sunkaraneni – 2020 – cs.utah.edu
… holding human-like conversations. Conversational agents have been implemented in the field of psychotherapy for a relatively long time, going back to chatbots such as ELIZA [49] or PARRY [9], which aim to simulate an agent conversing with a human participant …

Adaptive Fusion Techniques for Effective Multimodal Deep Learning
G Sahu – 2020 – uwspace.uwaterloo.ca
Page 1. Adaptive Fusion Techniques for Effective Multimodal Deep Learning by Gaurav Sahu A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Master of Mathematics in Computer Science Waterloo, Ontario, Canada, 2020 …

Explaining Natural Language query results
D Deutch, N Frost, A Gilad – The VLDB Journal, 2020 – Springer
Multiple lines of research have developed Natural Language (NL) interfaces for formulating database queries. We build upon this work, but focus on presenting a highly detailed form of the answersin…

Brain-inspired Search Engine Assistant based on Knowledge Graph
X Zhao, H Chen, Z Xing, C Miao – arXiv preprint arXiv:2012.13529, 2020 – arxiv.org
Page 1. Brain-inspired Search Engine Assistant based on Knowledge Graph Xuejiao Zhao1,2, Huanhuan Chen3, Zhenchang Xing4, Chunyan Miao1,2,? 1Joint NTU-UBC Research Centre of Excellence in Active Living for the …

Fuzzification of Supervised and Semi-Supervised Convolution Neural Networks for Identification of Neutral Text in Sentiment Analysis
R Najar – 2020 – search.proquest.com
… ees to business data, charts, and different information extracted from the business text data. Chat-bots have revolutionized the customer service sector by helping answer customers’ questions, directing users to guides and manuals, or re-routing requests …

Detecting Abuse on the Internet: It’s Subtle
S Bagga – 2020 – search.proquest.com
Page 1. Detecting Abuse on the Internet: It’s Subtle Sunyam Bagga Master of Science School of Computer Science McGill University Montreal, Quebec December, 2019 A thesis submitted to McGill University in partial fulfillment …

Scalable Text Analysis with Efficient Distributed Word Representation
Z Xue – 2020 – escholarship.org
… 2021 Zijun Xue, Ting-Yu Ko, Neo Yuchen, Ming-Kuang Wu, Chu-cheng Hsieh. “Isa: Intuit Smart Agent, A Neural-Based Agent-Assist Chatbot” Accepted by ICDM 2018 Demo Session Zijun Xue, Ruirui Li, Mingda Li. “Recent Progress in Converesational AI.” Accepted by KDD …

Automating Knowledge Distillation and Representation from Richly Formatted Data
S Wu – 2020 – search.proquest.com
… A multi-task learning model could make predictions for different tasks simultaneously while also benefit- ing from the shared underlying signals. Another example shown in Figure 2.4b is building a chatbot for customer service …

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