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Chatbot Analytics Based on Question Answering System and Deep Learning: Case Study for Movie Smart Automatic Answering

Jugal Shah, Computer Science Department, Lakehead University, Ontario, Canada, Sabah Mohammed*, Computer Science Department, Lakehead University, Ontario, Canada
2020 International Journal of Software Engineering and Its Applications  
The deep learning model employs a sequence-to-sequence (Seq2Seq) word embedding that was proposed by Ilya Sutskever in 2014, which had laid the foundation for building chatbot model build in this paper  ...  The Cornell Movie-Dialogs Corpus created at Cornell University, and Movie Dialog Dataset created at Facebook are preprocessed and used to train the chatbot.  ...  Sabah Mohammed for his support and supervision throughout this research project.  ... 
doi:10.21742/ijseia.2020.14.1.02 fatcat:tan3pq52xzbnvnoqafpidch6wa

AI Based Chatbot: An Approach of Utilizing On Customer Service Assistance [article]

Rejwan Bin Sulaiman
2022 arXiv   pre-print
The main objective project is to develop the chatbot solution that could comply with complex questions and logical output answers in a well-defined approach.  ...  The acceptance of this technology is increasing with the new improvements and efficiency of the chatbot system.  ...  In order to perform this action, there are multiple ways to do so, i.e. terms-weighting.  ... 
arXiv:2207.10573v1 fatcat:ip2zaxnulrb4nokfqr6eq5ql2q

Improving Access to Justice with Legal Chatbots

Marc Queudot, Éric Charton, Marie-Jean Meurs
2020 Stats  
For these people, accessing legal information is therefore critical. In this work, we attempt to tackle this problem by embedding legal data in a conversational interface.  ...  Both chatbots rely on various representations and classification algorithms, from mature techniques to novel advances in the field.  ...  Acknowledgments: The authors want to thank Me Stefanny Beaudoin for her support, guidance and help in understanding the legal domain.  ... 
doi:10.3390/stats3030023 fatcat:34xcb7433jh4jl5cnser6xu2fa

ConveRT for FAQ Answering [article]

Maxime De Bruyn, Ehsan Lotfi, Jeska Buhmann, Walter Daelemans
2021 arXiv   pre-print
Knowledgeable FAQ chatbots are a valuable resource to any organization.  ...  In this paper, we propose a novel pre-training procedure to adapt ConveRT, an English conversational retriever model, to other languages with less training data available.  ...  We also thank the reviewers for their helpful comments.  ... 
arXiv:2108.00719v3 fatcat:3pn6aa2rujayxcsoxopogtqi4e

Namah Subjective and Objective Aspects of Conversational Agent

Rajat Sharma, Mr. Ankur Sharma, Mr. Anurag Rana
2018 International Journal of Trend in Scientific Research and Development  
The feedback gathered from the studies will enable us to improve the applications in terms of service, performance and usability.  ...  Namah subjective and objective aspects of conversational agents focuses on the design and evaluation of Chatbot, a conversational agent for Natural Language Processing in An Android Application featuring  ...  Chatbot machinery is looking for patterns in collections of terms; each term is reduced to a token.  ... 
doi:10.31142/ijtsrd17063 fatcat:5uetaw5jsvfnxof43ilwx7misa

SlimMe, a Chatbot With Artificial Empathy for Personal Weight Management: System Design and Finding

Annisa Ristya Rahmanti, Hsuan-Chia Yang, Bagas Suryo Bintoro, Aldilas Achmad Nursetyo, Muhammad Solihuddin Muhtar, Shabbir Syed-Abdul, Yu-Chuan Jack Li
2022 Frontiers in Nutrition  
To our knowledge, this is the first chatbot designed with artificial empathy features, and it looks very promising in promoting long-term weight management.  ...  More user interactions and further data training and validation enhancement will improve the bot's in-built knowledge base and emotional intelligence base.  ...  The number of coherent and incoherent bot responses for each user input sentence can also reflect how relevant is the bot response for each question and how it matches the expected answer in the knowledge  ... 
doi:10.3389/fnut.2022.870775 pmid:35811989 pmcid:PMC9260382 fatcat:3febqkohwjb6nkomhu32zkmsjy

Review of State-of-the-Art Design Techniques for Chatbots

Ritu Agarwal, Mani Wadhwa
2020 SN Computer Science  
The evaluation metrics employed for chatbots are mentioned. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.  ...  This paper begins with an introduction of chatbots, followed by in-depth discussion on various classical or rule-based and neuralnetwork-based approaches.  ...  A.L.I.C.E [24] was the first chatbot based on AIML. The learning model used in ALICE is supervised one, i.e. it is being supervised by a person, the botmaster.  ... 
doi:10.1007/s42979-020-00255-3 fatcat:bfzjaknrvrgqjnuerijvxuo7uu

Adaptive e-Learning AI-Powered Chatbot based on Multimedia Indexing

Salma El Janati, Abdelilah Maach, Driss El
2020 International Journal of Advanced Computer Science and Applications  
However, the availability of a wide range of e-learning offers makes it difficult for learners to find the right content for their training needs.  ...  The core of our Chatbot is based on this indexed multimedia content which enables it to look for the information quickly. Then our designed Chatbot reduce response time and meet the learner's need.  ...  Learners must undergo continuous trainings in order to improve their skills and ensure technological monitoring [1] .  ... 
doi:10.14569/ijacsa.2020.0111238 fatcat:zapwayh73ne4hijp5tsz6fhuxu

Machine Learning in Healthcare Communication

Sarkar Siddique, James C. L. Chow
2021 Encyclopedia  
This includes chatbots for the COVID-19 health education, cancer therapy, and medical imaging.  ...  for complex dialogue management and conversational flexibility.  ...  Two very important factors in terms of patient care for physicians are knowledge and experience; however, in terms of gaining knowledge by cumulating data, humans are limited, but machine learning can  ... 
doi:10.3390/encyclopedia1010021 fatcat:k4fj32b7mvbbhljpezmsaxljj4

Automated Self-learning Chatbot Initially Build as a FAQs Database Information Retrieval System: Multi-level and Intelligent Universal Virtual Front-office Implementing Neural Network

Alessandro Massaro, Vincenzo Maritati, Angelo Galiano
2018 Informatica (Ljubljana, Tiskana izd.)  
The method proposed in this paper is based on dynamical information system capable toimplement a universal multi-level virtual front-office made by FAQs and chatbot self-learning systems.We describe statistics  ...  Povzetek: V prispevku je opisana nova metoda za izdelavo virtualnega asistenta iz arhiva vprašanj in odgovorov.  ...  Operators are able to improve the knowledge base and the overall performance of the system taking advantage of: • the archive of questions to which the chatbot does not respond (the training dataset is  ... 
doi:10.31449/inf.v42i4.2173 fatcat:7fd4lgx4mbfgppke4ftl3nqmwm

Recent Developments in Arabic Conversational AI: A Literature Review

Ahlam Fuad, Maha Al-Yahya
2022 IEEE Access  
Few surveys have targeted the conversational AI field for the Arabic language, and we aim to cover this gap with this study.  ...  We group them into three categories based on their functionality: (1) questionanswering (QA) systems, (2) task-oriented dialogue systems (DS), and (3) chatbots.  ...  For more information, see This article has been accepted for publication in a future issue of this journal, but has not been fully edited.  ... 
doi:10.1109/access.2022.3155521 fatcat:fujca4zpavbbjks2l4vquwvxii

KBot: a Knowledge graph based chatBot for natural language understanding over linked data

Addi Ait-Mlouk, Lili Jiang
2020 IEEE Access  
for a knowledge graph and data-driven chatbot.  ...  Making these data accessible and useful for end-users is one of the main objectives of chatbots over linked data.  ...  ACKNOWLEDGEMENT This research is funded by Umeå University in Sweden on federated database research  ... 
doi:10.1109/access.2020.3016142 fatcat:d5jjftfr4bgxpfp5d7opmemviy

A Literature Survey of Recent Advances in Chatbots

Guendalina Caldarini, Sardar Jaf, Kenneth McGarry
2022 Information  
However, there are many challenges and limitations in their application. In this survey we review recent advances on chatbots, where Artificial Intelligence and Natural Language processing are used.  ...  The increased benefits of chatbots led to their wide adoption by many industries in order to provide virtual assistance to customers.  ...  The knowledge base for this kind of model is usually formed by a database of question-answer pairs.  ... 
doi:10.3390/info13010041 fatcat:z6rpo3oogvhi5efzlanars7e6y

An Overview of Natural Language Processing

Mansi Agarwal
2019 International Journal for Research in Applied Science and Engineering Technology  
Natural Language Processing is a way for computers to analyze, understand, and derive meaning from human language in a smart and useful way.  ...  By utilizing Natural Language Processing, developers can organize and structure knowledge to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction  ...  Fig 4. 1 1 Machine learning in context of Natural language processing 4) Supervised Training : In supervised training, both the inputs and the outputs are provided. The network then processes the  ... 
doi:10.22214/ijraset.2019.5462 fatcat:ww4cgvbumre3bp5efckc2wvkjm

Chatbots: History, technology, and applications

Eleni Adamopoulou, Lefteris Moussiades
2020 Machine Learning with Applications  
It aims to organize critical information that is a necessary background for further research activity in the field of chatbots.  ...  After we present a complete categorization system, we analyze the two essential implementation technologies, namely, the pattern matching approach and machine learning.  ...  Acknowledgment This work is partially supported by the MPhil program ''Advanced Technologies in Informatics and Computers'', hosted by the Department of Computer Science, International Hellenic University  ... 
doi:10.1016/j.mlwa.2020.100006 fatcat:ezeuv56hizf3rfbo2ekb2yksiy
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