Named-Entity Recognition & Chatbots

Notes:

Named-Entity Recognition (NER) is a subfield of natural language processing (NLP) that involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, etc. NER is used to extract structured information from unstructured text data and is a crucial step in many NLP tasks such as information extraction, text summarization, question answering, and machine translation.

In dialog systems, NER is often used to extract important information from the user’s input and to understand the context and the intention behind the user’s utterance. For example, in a virtual assistant that helps users book a hotel room, NER can be used to identify the location, dates, and other relevant details mentioned in the user’s request and to use that information to search for available hotel rooms and present them to the user. NER can also be used to handle language ambiguity and to disambiguate words that can have multiple meanings depending on the context. For example, the word “bank” can refer to a financial institution or the edge of a river, and NER can help a dialog system to determine the correct interpretation based on the context.

Wikipedia:

Named-entity recognition

References:

Developing Enterprise Chatbots
B Galitsky – 2019 – Springer
… This book is intended to substantially improve chatbot engineering, providing the solid scientific background for building sophisticated dialogue systems. In particular, this book educates chatbot developers on building search engines for chatbots with linguistically-enabled …

A morpho-syntactically informed lstm-crf model for named entity recognition
L Simeonova, K Simov, P Osenova, P Nakov – arXiv preprint arXiv …, 2019 – arxiv.org
… known as Named Entity Disambiguation) task has been central in NLP research, the Named- entity recognition (NER) task … Language Processing (NLP) tasks such as Ques- tion Answering, Information Extraction, Machine Translation, Dialog Systems, and chatbots, where it …

Comparative Analysis of Approaches to Building Medical Dialog Systems in Russian
A Vatian, N Dobrenko, N Andreev… – … on Intelligent Data …, 2019 – Springer
… Quimbaya, AP, Munera, AS, Rivera, RAG et al.: Named entity recognition over electronic health records … Oyebode, OO, Orji, R.: Likita: a medical chatbot to improve healthcare delivery in Africa … P., Thommandram, A., Li, M., Fossat, Y.: Physicians’ perceptions of chatbots in health …

Generative Chat Bot Implementation Using Deep Recurrent Neural Networks and Natural Language Understanding
N Zalake, G Naik – … 2019: Conference on Technologies for Future …, 2019 – papers.ssrn.com
… Mechanism, Beam Search, BLEU Score, Deep Learning, Bidirectional RNN, Chatbot, Generative bots … Named Entity Recognition: The named entities in the data unnecessarily introduce bias in the … C. Jain, A. Nagvenkar, and K. Modi, “Production Ready Chatbots: Generate if not …

Peculiarities of Human Machine Interaction for Synthesis of the Intelligent Dialogue Chatbot
I Sidenko, G Kondratenko, P Kushneryk… – 2019 10th IEEE …, 2019 – ieeexplore.ieee.org
… solution is to use trained models of the type POS (part of speech) to identify parts of languages, and the NER (named entity recognition) system to … [21] S. Abbasi and H. Kazi, “Measuring Effectiveness of Learning Chatbot Systems on … [23] S. Raj, Building Chatbots with Python …

Towards understanding lifelong learning for dialogue systems
M Cieliebak, O Galibert, JM Deriu – … on Spoken Dialogue Systems …, 2019 – dreamboxx.com
… For instance, a chatbot for travel advice might be con- fronted with a new … and finally analyze, structure, and integrate the information into the chatbots’ knowledge base … is encouraged to learn different types of tasks (eg sentiment analysis, named entity recognition, etc) and …

Question Understanding Based on Sentence Embedding on Dialog Systems for Banking Service
KJ Oh, HJ Choi, S Kwon, S Park – 2019 IEEE International …, 2019 – ieeexplore.ieee.org
… to automate customer counseling service utilizing dialog system and chatbot in various … are additional 200 real input sentences from a commercial chat bot service platform … learning Based Boundary Detection and Dictionary Expansion for Named Entity Recognition in Dialogues …

A Study on Named Entity Recognition for Effective Dialogue Information Prediction
M Go, H Kim, H Lim, Y Lee, M Jee… – Journal of Broadcast …, 2019 – koreascience.or.kr
… Page 2. ??? ? 5?: ??? ?? ?? ??? ?? ??? ?? ?? 59 (Myunghyun Go et al.: A Study on Named Entity Recognition for Effective Dialogue Information Prediction) ?. ? ? … Oriented Dialogue System)? ??? ?? ?? ??? (ChatBot)?? ?? ? ?? …

Social Relation Extraction from Chatbot Conversations: A Shortest Dependency Path Approach
M Glas – SKILL 2019-Studierendenkonferenz Informatik, 2019 – dl.gi.de
… S-REX, a comparison method for extracting social relations from chatbot conversations … language conversations, used within chat messages between people, or humans and chatbots … type Person (PER) describes a person, recognized by a named entity recognition (NER) model …

Question-answering dialogue system for emergency operations
HY Chan, MH Tsai – International Journal of Disaster Risk Reduction, 2019 – Elsevier
… the dialogue system is Chinese and the system is implemented as a chatbot via LINE … Question analysis (QA) is similar to language understanding (LU) in a conventional dialogue system … There are two tasks in QA: named entity recognition (NER) and question classification (QC …

Conversational Chatbot System For Student Support In Administrative Exam Information
HA Rasheed, J Zenkert, C Weber, M Fathi – researchgate.net
… In named entity recognition, real world entities such as names, places and locations are identified in the free text … 8300 Page 8. [3] S. Abdul-Kader and Dr. John, “Survey on Chatbot Design Techniques in … [8] D. Jurafsky and J. Martin, “Dialog Systems and Chatbots,” Speech and …

Advances in natural language processing–a survey of current research trends, development tools and industry applications
KP Kalyanathaya, D Akila, P Rajesh – International Journal of …, 2019 – researchgate.net
… Most common type of conversation devices are Chatbots and Virtual Assistants … site and social media and then perform document classification and named entity recognition to filter … In document search applications, the banks or financial institutions uses chatbot interface that …

Chatbots Assisting German Business Management Applications
F Steinbauer, R Kern, M Kröll – International Conference on Industrial …, 2019 – Springer
… Benikova, D., Yimam, SM, Santhanam, P., Biemann, C.: GermaNER: free open German named entity recognition tool … Kowalke, P.: How chatbots will change Customer Relationship Management (2017)Google Scholar. 11 … Thomas, NT: An e-business chatbot using AIML and LSA …

Chatbot Components and Architectures
B Galitsky – Developing Enterprise Chatbots, 2019 – Springer
… This module consists of a Named Entity Recognition and Disambiguation (NER) model and a template selection model … For example, if the entity is a movie director, the chatbot retrieves the director’s gender, age, acted films list; if the entity is a city, the chatbots gets its …

Survey of Textbased Chatbot in Perspective of Recent Technologies
B Som, S Nandi – … Conference, CICBA 2018, Kalyani, India, July …, 2019 – books.google.com
… The other is the word-level information extraction such as named entity recognition and slot filling … ISSN 2321-3469 Mobgea: The Power of Chatbots: The art of Conversation. White Paper (2017) Shah, V.: Autopsy of a Chatbot: The 7 core components needed for a successful …

Real-World Conversational AI for Hotel Bookings
B Li, N Jiang, J Sham, H Shi… – 2019 Second International …, 2019 – ieeexplore.ieee.org
… Index Terms—conversational AI, task-oriented chatbot, named entity recognition, information retrieval … RELATED WORK Numerous task-oriented chatbots have been developed for commercial and … CHATBOT ARCHITECTURE Our chatbot system tries to find a desirable hotel for …

Ensemble-based deep reinforcement learning for chatbots
H Cuayáhuitl, D Lee, S Ryu, Y Cho, S Choi, S Indurthi… – Neurocomputing, 2019 – Elsevier
… 10], [11], [12], [13], [14], [15], policy-based methods have been particularly applied to open-ended dialogue systems such as (chitchat) chatbots [5], [6], [16]. This is not surprising given the fact that task-oriented dialogue systems use finite action sets, while chatbot systems use …

Survey on Out-Of-Domain Detection for Dialog Systems
YS Jeong, YM Kim – Journal of Convergence for Information …, 2019 – koreascience.or.kr
… needs to intelligent conversational agent, which is also typically called as chatbot or dialog … analysis, Part-Of-Speech (POS) tagging, shallow parsing (ie, chunking), Named Entity Recognition (NER), syntactic … direction is to construct a public dataset for the dialog system, and this …

Automating Chalkboard support processes using a chatbot
JPY Brown-Pobee – 2019 – air.ashesi.edu.gh
… access the dialog system. The primary use cases for which the chatbot is being built are … task. Literature Review on Chatbots and Dialog Systems: Books such as Speech and Language … Entity Extraction RASA uses Named Entity Recognition using Conditional Random Fields …

Emergency Patient Care System Using Chatbot
P Raj, R Murali Krishna, SM Krishna, KH Vardhan… – ijtre.com
… first aid, offering a solution for simpler medical issues: these are all possible situations for chatbots to step … Named Entity Recognition: The medical chatbot looks for categories of words, like the name of the product, the user?s … “An Approach to Enhance Chatbot Semantic Power …

A chatbot for the banking domain
P Schmidtová – 2019 – dspace.cuni.cz
… Abstract: This thesis designs, implements and evaluates a task-based chat- bot, which is expected to answer questions and give advice from the banking domain … This thesis presents a fully task-oriented chatbot. We can also divide chatbots based on their implementation …

Improving NLU Training over Linked Data with Placeholder Concepts
T Schmitt, C Kulbach, Y Sure-Vetter – International Conference on …, 2019 – library.oapen.org
… Our contribution in training an NLU targets the research field of chatbots, as well … While most chatbot frameworks (IBM Watson, Microsoft Bot Ser- vice) are based on … to link these static approaches by generalizing SQA into 3 steps (Named Entity Recognition and Disambiguation …

Learning to Memorize in Neural Task-Oriented Dialogue Systems
CS Wu – arXiv preprint arXiv:1905.07687, 2019 – arxiv.org
… performance. xiii Page 14. Chapter 1 Introduction 1.1 Motivation and Research Problems Dialogue systems, known as conversational agents or chatbots, can communicate with human via natural language to assist, inform and entertain people. They have become increasingly …

Deep learning based chatbot models
R Csaky – arXiv preprint arXiv:1908.08835, 2019 – arxiv.org
… they are limited to a specific domain, thus users have to be guided by the dialog system towards the task … The second type of dialog agents are the non-task or open-domain chatbots … This means that one should hardly be able to distinguish such a chatbot from a real human, but …

Chatbot in English Classrooms
M Vogel, I Nussbaumer – fhnw.ch
… The named entity recognition (NER) component identifies real world objects in tokens … to the development of a chatbot for an ESL setting: While the chatbot relies on correct language input, learners tend to disregard language rules when communicating with chatbots …

CHEERBOT: A Step Ahead of Conventional ChatBot
CB Maniyar, CM Bhatt, TN Pandit… – Next-Generation Wireless …, 2019 – igi-global.com
… analysis: Word and text tokenizer • n-gram and collocations • Part-of-speech tagger • Tree model and Text chunker for capturing • Named-entity recognition … Retrieved from https://apps.worldwrit- able.com/tutorials/chatbot … Two case studies in using chatbots for security training …

IrideR G: an Industrial Perspective on Production Grade End To End Dialog System
C Giannone, V Bellomaria, A Favalli, R Romagnoli – 2019 – ceur-ws.org
… 2018. Transfer learning for industrial appli- cations of named entity recognition. 12 … 2019. Convlab: Multi-domain end-to-end dialog system platform … 2017. Sequential matching network: A new architecture for multi-turn response selection in retrieval-based chatbots …

Intelligent Chatbot for Requirements Elicitation and Classification
CSRK Surana, DB Gupta… – 2019 4th International …, 2019 – ieeexplore.ieee.org
… Python’s Sklearn machine learning library is used for the classification, and spaCy English language model is used for Named Entity Recognition … Programming challenges of chatbot: Current and future prospective … [10] Khan, R. and Das, A., 2018. Build Better Chatbots. Apress …

Knowledge-incorporating ESIM models for response selection in retrieval-based dialog systems
J Ganhotra, SS Patel, K Fadnis – arXiv preprint arXiv:1907.05792, 2019 – arxiv.org
… architecture that makes use of similar conversations for the generation-based dialog system and achieved … Work In this paper, we introduced two knowledge incorporating end-to-end dialog systems for retrieval … Boosting named entity recognition with neural character embeddings …

Deep learning for spoken dialogue systems: application to nutrition
MB Korpusik – 2019 – dspace.mit.edu
… 31 1.1 Dialogue Systems … List of Figures 1-1 A standard pipeline for a spoken dialogue system, where the input spoken user query is passed to an automatic speech recognizer to generate its text … 65 4-2 An illustration of how BERT is used for named entity recognition, or se …

Natural Language Understanding in Smartdialog: A Platform for Vietnamese Intelligent Interactions
NTT Trang, NH Ky, H Son, NT Hung… – Proceedings of the 2019 …, 2019 – dl.acm.org
… such as virtual assistant eg Siri, Alexa, Cortana, Google Assistant [2], chat bot eg Chatfuel … Hands-On Chatbots and Conversational UI Development: Build chatbots and voice … M Friedrich, Juliane Fluck, and Martin Hofmann-Apitius, “Named Entity Recognition with Combinations …

Social Media and Chatbots use for chronic disease patients support: case study from an online community regarding therapeutic use of cannabis
AR Teixeira – 2019 – repositorio-aberto.up.pt
… discussing the therapeutic use of cannabis for chronic diseases? • What contributions can a chatbot offer to improve this dynamic beyond technical limitations … making, online health communities and health related chatbots …

Self-Attentional Models Application in Task-Oriented Dialogue Generation Systems
MS Mehrjardi, A Trabelsi, OR Zaiane – arXiv preprint arXiv:1909.05246, 2019 – arxiv.org
… 2https://github.com/msaffarm/chatbot-exp … For example, in the restau- rant domain chatbots common entities are meal, restaurant name, date, time and the number of peo- ple … To evaluate our models we could use named-entity recognition evaluation metrics (Jiang et al., 2016) …

NLP-based chatbot for HAMK
D Trifunovic – 2019 – theseus.fi
… JavaScript Object Notation KPI Key Performance Indicator LUIS Language Understanding Intelligent Service NER Named Entity Recognition NLP Natural … How can the administrative effort be reduced by the chatbot operation … 2 2 ARTIFICIAL INTELLIGENCE AND CHATBOTS …

Anniversary article: Then and now: 25 years of progress in natural language engineering
J Tait, Y Wilks – Natural Language Engineering, 2019 – search.proquest.com
… was considerably more computationally demanding than the shallow pat- tern matching techniques used by Colby in PARRY, and used by other later chatbots … Probably most notable is the widespread use of named entity recognition and tracking. Another is chatbot technology …

Transfer Hierarchical Attention Network for Generative Dialog System
X Zhang, Q Yang – International Journal of Automation and Computing, 2019 – Springer
… The Chit-chat dialog system is a promising natural language processing (NLP) technology which aims to en- able computers to chat with human through natural lan- guage. Traditional chit-chat dialog systems are built by hand-crafted rules or directly selecting a human writing …

Training Set Expansion Using Word Embeddings for Korean Medical Information Extraction
YM Kim – … Data Management, Polystores, and Analytics for …, 2019 – Springer
… Reinforcement learning will be a good option for the dialogue system … is partially supported by two projects, Smart Multimodal Environment of AI Chatbot Robots for … 1. Bontcheva, K., Derczynski, L., Roberts, I.: Crowdsourcing named entity recognition and entity linking corpora …

Business AI alignment modeling based on enterprise architecture
H Takeuchi, S Yamamoto – Intelligent Decision Technologies 2019, 2019 – Springer
… an evaluation metric was proposed [13] to evaluate a dialog system used in a chatbot, it was noted that it is difficult to evaluate a dialog system generally [9 … We applied the proposed generic EA to a real project where we used a named entity recognition technology for an …

Samvaadhana: A Telugu Dialogue System in Hospital Domain
SR Duggenpudi, KSS Varma, R Mamidi – … of the 2nd Workshop on Deep …, 2019 – aclweb.org
… There is no read- ily available computational tool for Named Entity Recognition in Telugu for our domain … 2019. Spoken dialogue system using recognition of user’s feedback for rhythmic dialogue. Page 8. 241 Metric Description … Gotora. 2017. A neural-network based chat bot …

Unsupervised dialogue intent detection via hierarchical topic model
A Popov, V Bulatov, D Polyudova… – Proceedings of the …, 2019 – aclweb.org
… Abstract One of the challenges during a task- oriented chatbot development is the scarce availability of the labeled training data … More universal and robust dialogue systems should work without any supervision or defined rules … 4.2 Named entity recognition …

#MeTooMaastricht: Building a chatbot to assist survivors of sexual harassment
T Bauer, E Devrim, M Glazunov, WL Jaramillo… – … Conference on Machine …, 2019 – Springer
… as rule-based (scripted) or end-to-end (usually based on deep learning) chatbots … Named entity recognition (NER) was implemented by finetuning BERT state-of-the-art model enhanced by … fellow at Brandeis University, in building the dialogue flow of the chatbot implemented in …

Conversational AI: An Overview of Methodologies, Applications & Future Scope
P Kulkarni, A Mahabaleshwarkar… – 2019 5th …, 2019 – ieeexplore.ieee.org
… A multiclass classification method based on deep learning for named entity recognition in electronic medical records … A Survey on Conversational Agents/Chatbots Classification and Design Techniques … 1525-1530Silvia. [25] Q., Suresh M., A Chatbot-based Interactive Question …

FASTDial: Abstracting Dialogue Policies for Fast Development of Task Oriented Agents
SS Tekiroglu, B Magnini, M Guerini – … of the 57th Annual Meeting of the …, 2019 – aclweb.org
… 2017. Dialog sys- tems and chatbots. Speech and language processing … 2018. Explor- ing named entity recognition as an auxiliary task for slot filling in conversational language understand- ing … 2017. Pydial: A multi- domain statistical dialogue system toolkit …

A hybrid convolutional and recurrent network approach for conversational AI in spoken language understanding
IMTL Douai – Fourth Conference on Software Engineering and …, 2019 – seim-conf.org
… of the users queries when communicating with the users in a natural way throw these chatbots … Before the era of deep learning the task of Named Entity Recognition (NER) was solved using grammars-based models … But still, in the w ay to implement a full chatbot, we will need to …

Deep neural architecture with character embedding for semantic frame detection
FZ Daha, S Hewavitharana – 2019 IEEE 13th International …, 2019 – ieeexplore.ieee.org
… has many applications and has been useful for systems like chat bots [1], question … representation has been used in some recent work, especially in Named-Entity Recognition (NER) … Ilievski, C. Musat, A. Hossmann, and M. Baeriswyl, “Goal- oriented chatbot dialog management …

Identifying facts for chatbot’s question answering via sequence labelling using recurrent neural networks
M Nuruzzaman, OK Hussain – Proceedings of the ACM Turing …, 2019 – dl.acm.org
… NLP) that not yet solved completely [1]. In recent years, both academic and industry showed interests in chatbot, which is … For instance, in named entity recognition, a sentence like “Yesterday, Dr Omar Hussain gave a speech.” contains example one named entity (“Omar Hussain …

Automatic Ontology Population Using Deep Learning for Triple Extraction
MH Su, CH Wu, PC Shih – 2019 Asia-Pacific Signal and …, 2019 – ieeexplore.ieee.org
… Therefore, ontology is useful for a chatbot system [14]-[15] … This task is like the Named Entity Recognition (NER) task … [10] N. Mehta, R. Gupta, A. Raux, D. Ramachandran, and S. Krawczyk, “Probabilistic ontology trees for belief tracking in dialog systems,” Proc …

A Scheme for Factoid Question Answering over Knowledge Base
B HAPPY, T AMAGASA – db-event.jpn.org
… Recently, Question Answering has also been applied in developing chat- bots[1] and … References [1] S. Quarteroni, ”A chatbot-based Interactive Question An- swering System … [27] Jenny R. Finkel, Christopher D. Manning, ”Nested named entity recognition,” Proceedings of the …

An Architecture for Dynamic Conversational Agents for Citizen Participation and Ideation
S Ahmed – researchgate.net
… There are multiple platforms for Named Entity Recognition, most notably GATE1, OpenNLP 2 … Slots In the context of Chatbots, Slots are variables a Chatbot requires to perform a specific task … A single utterance is an entire sentence passed as input to the Chatbot to intent …

Proceedings of the 2019 Workshop on Widening NLP
A Axelrod, D Yang, R Cunha, S Shaikh… – Proceedings of the 2019 …, 2019 – aclweb.org
… Implementing a Multi-lingual Chatbot for Positive Reinforcement in Young Learners … Augmenting Named Entity Recognition Systems with Commonsense Knowledge Gaith Dekhili, Tan Ngoc Le and … Exploring Social Bias in Chatbots using Stereotype Knowledge Nayeon Lee …

Transforming the communication between citizens and government through AI-guided chatbots
A Androutsopoulou, N Karacapilidis, E Loukis… – Government Information …, 2019 – Elsevier
… Through a proper incorporation of AI-based building blocks, the abovementioned services add intelligence to the functionality and user interfaces of existing chatbots (and chatbot builders), the ultimate aim being to enable citizens to fully control the conversation they have with …

Katecheo: A Portable and Modular System for Multi-Topic Question Answering
S Hirekodi, S Sunny, L Topno, A Daniel… – arXiv preprint arXiv …, 2019 – arxiv.org
… When people interact with chatbots, smart speak- ers or digital assistants (eg, Siri1), one of … It would be advanta- geous for such a chatbot to answer questions about food and … each topic, the user supplies the sys- tem with a pre-trained Named Entity Recognition (NER) model …

Expanding on the end-to-end memory network for goal-oriented dialogue
PA Taraldsen, V Vatne – 2019 – uia.brage.unit.no
… of the Dialog System Technology Challenge: building an end- to-end dialog system for goal … term memory layer at the beginning of the model used for named entity recognition, to capture … In: Workshop: Chatbots for Social Good, September 3, 2019, Paphos, Cyprus (under review …

Question Generalization in Conversation
J Peng, S Zhong, P Li – … Symposium on Artificial Intelligence and Robotics, 2019 – Springer
… A. Named entity recognition … At the same time, we use the probability-triggered interleaving combination mechanism to control the chat-bot to actively and … However, the current chat bots can’t reach the level of human intelligence, and simply using the probabilistic trigger …

Slugbot: Developing a computational model andframework of a novel dialogue genre
KK Bowden, J Wu, W Cui, J Juraska, V Harrison… – arXiv preprint arXiv …, 2019 – arxiv.org
… Discourse coherence in SCRIPT MODEL dialogue systems is created by the user interaction designer … Other existing retrieval based chatbots also operate on large existing corpora such as … Negative users, we would suggests some resources in our dialogue system to improve …

Knowledge Creation Model for Emotion Based Response Generation for AI
UK Premasundera, MC Farook – 2019 19th International …, 2019 – ieeexplore.ieee.org
… Zhou and colleagues [21] at Tsinghua University in Beijing have developed a chatbot that can evaluate the emotional … Generally, in Natural Language Processing (NLP); Named- entity recognition (NER) is used to extract entities … 22] A. Pardes, “The Emotional Chatbots Are Here …

Modeling Machine Learning Agent for Interaction Conversational System Using Max Entropy Approach in Natural
AK Negi, SI Hassan – Data Communication and Networks …, 2019 – books.google.com
… required where user come and interact with machine learning chatbot for registering his … Modeling Machine Learning Agent… 221 1.4 NER (Named Entity Recognition) This is also known as … First, the computer and human dialogue system where they both understand each other …

FastText-Based Intent Detection for Inflected Languages
K Balodis, D Deksne – Information, 2019 – mdpi.com
… used for speech recognition and generation, machine translation, text classification, named entity recognition, text generation … amount of training data, which is not the typical case for chatbots … The chatbot dataset contains users’ questions from a Telegram chatbot that answers …

Self-Attentional Models Application in Task-Oriented Dialogue Generation Systems
M Saffar Mehrjardi – 2019 – era.library.ualberta.ca
… MLP Multi-Layer Peceptron NER Named-entity Recognition NLG Natural Language Generation … engaged when they feel that they have become friends with the chatbot. Ama … chatbots, and customer-service chatbots. Deployment of task-oriented chat …

NLP commercialisation in the last 25 years
R Dale – Natural Language Engineering, 2019 – cambridge.org
… Today’s text-based chatbots, found on … this topic are as relevant today (and should be on the bookshelf of every dialog or chatbot developer), as … MUC conferences were key to defining and developing this area of technology, with an early initial focus on named entity recognition …

Stacked Multi-head Attention for Multi-turn Response Selection in Retrieval-based Chatbots
C Yu, W Jiang, D Zhu, R Li – 2019 Chinese Automation …, 2019 – ieeexplore.ieee.org
… we intend to improve the performance of the model by means of named entity recognition, syntax analysis … Y. Dianhai, and W. Hua, “Multi-turn response selection for chatbots with deep … corpus: A large dataset for research in unstructured multi-turn dialogue systems,” in SIGDIAL …

Standardization of Robot Instruction Elements Based on Conditional Random Fields and Word Embedding
H Wang, Z Zhang, J Ren, T Liu – Journal of Harbin Institute of …, 2019 – hit.alljournals.cn
… destination, transportation, accommodation, etc., and also different from ordinary chatbots which usually … the experiments verified the proposals, and the respond of the dialog system to human … Conditional random fields with semantic enhancement for named-entity recognition …

Knowledge graph construction and applications for Web search and beyond
P Wang, H Jiang, J Xu, Q Zhang – Data Intelligence, 2019 – MIT Press
… applications of knowledge graph in Sogou Inc.: entity detection and linking, knowledge-based question answering and knowledge-based dialog system … For named entity recognition and linking tasks, we train a Bi-LSTM-CRF model and the feature and parameter selection …

Follow-up Question Generation
Y Mandasari – 2019 – essay.utwente.nl
… NER Named Entity Recognition NLG Natural Language Generation … a specific task such as reservation of the restaurant. Generally, chatbots carry an en … Chatbot architectures are generally distinguished into two classes: rule-based systems and corpus-based systems …

Deep learning for nlp and speech recognition
U Kamath, J Liu, J Whitaker – 2019 – Springer
… multi- task learning techniques extensively. This case study explores multitask learning techniques for NLP tasks such as part-of-speech tagging, chunking, and named entity recognition and analysis. Readers should expect to …

Ranking of Potential Questions
L Schricker, T Scheffler – Proceedings of the 57th Annual Meeting of the …, 2019 – aclweb.org
… For linguistic processing spaCy (Honni- bal and Montani, 2019) (eg dependency pars- ing, named entity recognition and POS tagging), NLTK … linguis- tic theories, but might also be useful in dialogue generation applications, eg for machine dialogue systems and chatbots …

MSc in Computer Science
RB Sulaiman – researchgate.net
… 2.6.3.3 N-GRAMS ….. 31 2.6.3.4 NAMED ENTITY RECOGNITION (NER) …. 32 … Chatbot technology ? Types of chatbot ? Comparison of chatbots ? Functions of chatbot ? Syntactic analysis …

Towards a Decentralized, Trusted, Intelligent and Linked Public Sector: A Report from the Greek Trenches
T Beris, I Angelidis, I Chalkidis, C Nikolaou… – … Proceedings of The …, 2019 – dl.acm.org
Page 1. Towards a Decentralized, Trusted, Intelligent and Linked Public Sector: A Report from the Greek Trenches Themis Beris Dept. of Informatics and Telecommunications, National and Kapodistrian University of Athens Athens, Greece tberis@di.uoa.gr Iosif Angelidis Dept …

Comparison of Named Entity Recognition Tools Applied to News Articles
S Vychegzhanin, E Kotelnikov – 2019 Ivannikov Ispras Open …, 2019 – ieeexplore.ieee.org
… 7. DeepPavlov [10] – a framework for chatbots and virtual assistants development … [9] M. Won, P. Murrieta-Flores and B. Martins, “Ensemble Named Entity Recognition (NER): Evaluating … M. Zaynutdinov, “DeepPavlov: Open-Source Library for Dialogue Systems”, in Proceedings …

“I think it might help if we multiply, and not add”: Detecting Indirectness in Conversation
P Goel, Y Matsuyama, M Madaio, J Cassell – … on Spoken Dialogue System …, 2019 – Springer
… Tutoring Agent or a general-purpose socially-aware spoken dialogue system [30] that … in interpersonal communication, incorporating its detection in spoken dialogue systems may ultimately … R (2015) Multimedia lab@ acl w-nut ner shared task: named entity recognition for twitter …

Natural Language Processing, Understanding, and Generation
A Singh, K Ramasubramanian, S Shivam – Building an Enterprise Chatbot, 2019 – Springer
… Functions. Identify part of speech, text categorizing, named entity recognition, translation, speech recognition … Architecture diagram for chatbots. Let’s say an airline company has built a chatbot to book a flight via their website or social media pages …

Question generation based on chat?response conversion
SH Zhong, J Peng, P Liu – Concurrency and Computation: Practice … – Wiley Online Library
… However, the responses proposed by the chat?bot are only a passive answer or assentation, which does not arouse the desire … We convert the normal output from chat bots into a question sentence that can change the robot from a passive response … A. Named entity recognition …

A survey on question answering systems over linked data and documents
E Dimitrakis, K Sgontzos, Y Tzitzikas – Journal of Intelligent Information …, 2019 – Springer
… We can distinguish such systems to chatbots which are used mainly for fun … Spoken Dialogue Systems A Spoken Dialogue System (SDS) is a computer system that takes as … Semantic Identification and labeling of arguments in the text Named Entity Recognition Named Entity …

Automatically responding to customers
R Huijzer – pure.tue.nl
… The IBM sales department claims that Autodesk using chatbots cut down their resolution time “from 1.5 days to 5.4 minutes for most inquiries” [46] … Often the chatbot needs to know more than just the intent … Named-entity recognition (NER) can be used to find this information …

Exploring machine learning and deep learning frameworks for task-oriented dialogue act classification
T Saha, S Srivastava, M Firdaus, S Saha… – … Joint Conference on …, 2019 – ieeexplore.ieee.org
… Applications such as online chat-bots that include the Problem Solving Agent, Conversational Agent, etc … set is proposed which is more appropriate for building a chat-bot system … success in solving many sequence labeling prob- lems such as Named Entity Recognition (NER) [18 …

Discourse-Level Dialogue Management
B Galitsky – Developing Enterprise Chatbots, 2019 – Springer
… Entity extraction, also known as entity name extraction or named entity recognition, is an information … 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 …

Computational linguistics: Introduction to the thematic issue
A Gelbukh – Computación y Sistemas, 2019 – cys.cic.ipn.mx
… Japan and Turkey in her paper “Joint Learning of Named Entity Recognition and Dependency … They write: Retrieval- based dialogue systems converse with humans by ranking candidate … Word Embeddings” write: In goal-oriented conversational agents like Chatbots, finding the …

Employing Conversational Agents in Palliative Care: A Feasibility Study and Preliminary Assessment
M Chatzimina, L Koumakis, K Marias… – 2019 IEEE 19th …, 2019 – computer.org
… wit.ai, ,•, ,ner_crf: a component which is a pre-trained spacy named ,entity recognition model that … 17] ,NM Radziwill and MC Benton, “Evaluating Quality of ,Chatbots and Intelligent … D. Ireland ,et al.,, “Hello harlie: Enabling speech monitoring ,through chat-bot conversations,” ,Stud …

Question Generation with Adaptive Copying Neural Networks
X Lu – 2019 – curve.carleton.ca
… 23 2.14 An example of dialog system [7]. . . . 24 … For example, dialog systems in chatbots are currently drawing significant attention. Siri, Apple’s voice assistant, is a good application of chatbots that can talk with people as if they were human …

Rotational unit of memory: A novel representation unit for rnns with scalable applications
R Dangovski, L Jing, P Nakov, M Tatalovi?… – Transactions of the …, 2019 – MIT Press
… RNNs), which have become a standard tool for addressing a number of tasks ranging from language modeling, part-of-speech tagging and named entity recognition to neural machine translation, text summarization, question answering, and building chatbots/ dialog systems …

ANA at SemEval-2019 Task 3: Contextual Emotion detection in Conversations through hierarchical LSTMs and BERT
C Huang, A Trabelsi, OR Zaïane – arXiv preprint arXiv:1904.00132, 2019 – arxiv.org
… In such cases, a user is conversing with an automatic chatbot. Empowering the chat- bot with the ability to detect the user’s emotion is a step forward towards the construction of an emo … It has shown great success in word similarity tasks and Named Entity Recognition benchmarks …

Sémantické porozum?ní konverzaci
P Lorenc – 2019 – dspace.cvut.cz
… The chatbots are used to cooperate with humans to fasten the conversation or replace the … a central component of the conversation AI system, we classify intent, do named entity recognition, analyze the … In some cases, for example in chatbot system Alquist2, we require to catch …

Neural Generation for Czech: Data and Baselines
O Dušek, F Jur?í?ek – arXiv preprint arXiv:1910.05298, 2019 – arxiv.org
Page 1. In Proceedings of INLG, Tokyo, Japan, October 2019. Neural Generation for Czech: Data and Baselines Ondrej Dušek and Filip Jurc?cek Charles University, Faculty of Mathematics and Physics Institute of Formal and …

Toward Understanding the Impact of Artificial Intelligence on Education: An Empirical Research in Japan
Y Takahashi, P Vate-U-Lan – ECIAIR 2019 European Conference …, 2019 – books.google.com
… The AI eLearning application implements a voice chatbot with speech syntheses … to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction … SimpleDS: A Simple Deep Reinforcement Learning Dialogue System, in: Jokinen, K …

A Comparative Study of Classical and Deep Classifiers for Textual Addressee Detection in Human-Human-Machine Conversations
O Akhtiamov, D Fedotov, W Minker – International Conference on Speech …, 2019 – Springer
… useful for SDSs, such as personal assistants, social robots, and chat bots, and may … off-talk detection based on text classification within an automatic spoken dialogue system … N., Radford, W., Murphy, T., Curran, JR: Learning multilingual named entity recognition from Wikipedia …

TUM Data Innovation Lab
H Agarwala, R Becker, M Fatima, L Riediger, A Belitski… – 2019 – di-lab.tum.de
… NER (Named Entity Recognition) tagging locates and classifies entities in unstructured data … The potential is quite big as developers could improve their chatbots over time … It also provides the flexibility to modify the pipeline and deploy the entire chatbot from personal servers …

Discovering the Functions of Language in Online Forums
Y Ismaeil, O Balalau, P Mirza – Proceedings of the 5th Workshop on …, 2019 – aclweb.org
… Morrison and Martens (2018) incorporate the phatic function in a dialog system that would fol- low social … an emotive message calls for a thoughtful and empathetic response) are beneficial for building smarter chatbots … Named entity recognition in tweets: An ex- perimental study …

ScratchThat: Supporting Command-Agnostic Speech Repair in Voice-Driven Assistants
J Wu, K Ahuja, R Li, V Chen, J Bigham – Proceedings of the ACM on …, 2019 – dl.acm.org
… proper nouns. We accommodate this by augmenting the parameter identification with named entity recognition (NER) models and a user-specific list of known entities (eg, list of users’ songs, contacts). 3.2.1 Chunking. Chunking …

Proposed Model for Arabic Grammar Error Correction Based on Convolutional Neural Network
A Solyman, Z Wang, Q Tao – 2019 International Conference on …, 2019 – ieeexplore.ieee.org
… basis for future ALNP projects such as text generation, dialog systems, and semantic … has successfully applied in applications such as online chatbots, Google Translate … A. Hartley, “Improving machine translation quality with automatic named entity recognition,” in Proceedings …

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language …
K Inui, J Jiang, V Ng, X Wan – Proceedings of the 2019 Conference on …, 2019 – aclweb.org
Page 1. EMNLP-IJCNLP 2019 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing Proceedings of the Conference November 3–7, 2019 Hong Kong, China Page 2 …

Towards the Learning, Perception, and Effectiveness of Teachable Conversational Agents
N Chhibber – 2019 – uwspace.uwaterloo.ca
… 19 3.3.2 Dialog System … Since then, researchers have explored the use of active learning with support vector machines [125], Bayesian networks [124], named entity recognition [102], and natural language processing [103] …

Nlsc: Unrestricted natural language-based service composition through sentence embeddings
OJ Romero, A Dangi, SA Akoju – 2019 IEEE International …, 2019 – ieeexplore.ieee.org
… Index Terms—Service composition, Middleware, Sentence Em- beddings, Named-Entity Recognition, Effort Estimation. NLP … WM is implemented as a Hash Table or Dictionary. Data type disambiguation: we disambiguate data types by using named-entity recognition …

The artificial facilitator: guiding participants in developing causal maps using voice-activated personal assistant
S Reddy, T Reddy – 2019 – knowledgecommons.lakeheadu.ca
… significant differences across systems. Unlike chat-bots, smart conversa … design is so common that the system may be presented as a slot-based dialogue system [55] … This paper [58] describes an approach to the automatic construction of Named Entity Recognition(NER) …

Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
A Korhonen, D Traum, L Màrquez – … of the 57th Annual Meeting of the …, 2019 – aclweb.org
Page 1. ACL 2019 The 57th Annual Meeting of the Association for Computational Linguistics Proceedings of the Conference July 28 – August 2, 2019 Florence, Italy Page 2. Diamond Sponsors: Platinum Sponsors: ii Page 3. Gold sponsors: Keiosk Analytics Silver sponsors …

Natural Language Processing and Chinese Computing: 8th CCF International Conference, NLPCC 2019, Dunhuang, China, October 9–14, 2019 …
J Tang, MY Kan, D Zhao, S Li, H Zan – 2019 – books.google.com
Page 1. Jie Tang· Min-Yen Kan · Dongyan Zhao · Sujian Li· Hongying Zan (Eds.) Natural Language Processing and Chinese Computing 8th CCF International Conference, NLPCC 2019 Dunhuang, China, October 9–14, 2019 Proceedings, Part I 123 Page 2 …

Learning Multilingual Semantic Parsers for Question Answering over Linked Data. A comparison of neural and probabilistic graphical model architectures
S Hakimov – 2019 – pub.uni-bielefeld.de
… 114 8.3.1 Named Entity Recognition … Some chatbots use NLU methods to interpret the intent of user messages, which increases the coverage by not relying on scripted inputs … Xiaoice3 is a chatbot developed by Microsoft that engages with users via chatting in Chinese language …

ICTAI 2019
YM Boumarafi, Y Salhi – computer.org
… and Adenilso Simao (Universidade de São Paulo, Brazil) xi Page 8. AERNs: Attention-Based Entity Region Networks for Multi-Grained Named Entity Recognition 408 Jianghai Dai (Beijing Institute of Technology, China), Chong …

Building Chatbots with Python
S Raj, S Raj, Karkal – 2019 – Springer
… Named-Entity Recognition … com as well as booking a table in a nearby restaurant of the hotel, but you can do that using your chatbot. Chatbots fulfill the need of being multipurpose and hence save a lot of time and money …

Cognitive Computing Recipes
A Masood, A Hashmi – Springer
Page 1. Cognitive Computing Recipes Artificial Intelligence Solutions Using Microsoft Cognitive Services and TensorFlow — Adnan Masood Adnan Hashmi Foreword by Matt Winkler Page 2. Cognitive Computing Recipes Artificial Intelligence Solutions Using …

A Systematic Approach for Automatically Answering General-Purpose Objective and Subjective Questions
LP Acharya – 2019 – repository.lib.fit.edu
… 1960s by the MIT Artificial Intelligence Laboratory to demonstrate the communication between humans and machines. Similar to a chatbot, ELIZA uses pattern matching and substitution methodologies to simulate conversations. DOCTOR is an example of a script …

Standardized representations and markup languages for multimodal interaction
R Tumuluri, D Dahl, F Paternò… – The Handbook of …, 2019 – dl.acm.org
Page 1. 9Standardized Representations and Markup Languages for Multimodal Interaction Raj Tumuluri, Deborah Dahl, Fabio Patern`o, Massimo Zancanaro 9.1 Introduction This chapter discusses some standard languages …

Contextual language understanding Thoughts on Machine Learning in Natural Language Processing
B Favre – 2019 – hal-amu.archives-ouvertes.fr
… General purpose dialog agents, also known as “chatbots”, are a good example of how humans can … The ELIZA chatbot (Weizenbaum 1976) or contestants to the Loeb- ner Prize competition (Stephens 2004 … Syntactic chunking or named entity recognition are instances of this task …

Voice assistants and how they affect consumer behavior
A Esmailzadeh, M Rolandsson – 2019 – odr.chalmers.se
… Cover: Image from Chatbots Magazine (2019). See bibliography for URL. Gothenburg, Sweden 2020 Page 5 … published in the 1950’s (Turning, 2009). Chatbots are described as “robots designed to simulate how a human would behave as a conversational partner”, and the …

Narrative Text Generation via Latent Embedding from Visual Stories
2019 – s-space.snu.ac.kr
Page 1.

Parsimonious Vole: a Systemic Functional Parser for English
E Costetchi – 2019 – media.suub.uni-bremen.de
… Relevant NLP tasks for gathering market intelligence are named entity recognition (NER), event extraction and sentence classification. With these tasks alone one can build a database … for extended insights. They deploy chat bots for increased responsiveness by providing …

Corpus linguistics for online communication: A guide for research
LC Collins – 2019 – books.google.com
… of most subsequent Chatbot interfaces and is now manifest in customer service chat relays online, even supported by Facebook Messenger and WhatsApp. When combined with speech recognition, such programming has led to the creation of dialogue systems on smartphone …