Survey on Intelligent Chatbots: State-of-the-Art and Future Research Directions

Almansor, EH; Hussain, FK

Survey on Intelligent Chatbots: State-of-the-Art and Future Research Directions

Almansor, EH Hussain, FK

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Publisher:: Springer
Publication Type:: Conference Proceeding
Citation:: Complex, Intelligent, and Software Intensive Systems, 2020, 993, pp. 534-543
Issue Date:: 2020-01-01

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Field	Value	Language
dc.contributor.author	Almansor, EH
dc.contributor.author	Hussain, FK
dc.date	2019-07-03
dc.date.accessioned	2021-05-05T06:09:14Z
dc.date.available	2021-05-05T06:09:14Z
dc.date.issued	2020-01-01
dc.identifier.citation	Complex, Intelligent, and Software Intensive Systems, 2020, 993, pp. 534-543
dc.identifier.isbn	9783030223533
dc.identifier.issn	2194-5357
dc.identifier.issn	2194-5365
dc.identifier.uri	http://hdl.handle.net/10453/148713
dc.description.abstract	Human-computer interaction (HCI) is an area of interest which plays a major role in understanding the interaction between humans and machines. Dialogue systems or conversational systems including chatbots, voice control interfaces and personal assistants are examples of HCI application that have been developed to interact with users using natural language. Chatbots can help customers find useful information for their needs. Thus, numerous organizations are using chatbots to automate their customer service. Thus, the needs for using artificial intelligence has been increasing due to the needs of automated services. However, devolving smart bots that can respond at the human level is challenging. In this paper, we survey the state-of-art chatbot approaches from based on the ability to generate appropriate responses perspective. After summarizing the review from this aspect, we identify the research issues and challenges in chatbots. The findings of this research will highlight directions for future work.
dc.language	en
dc.publisher	Springer
dc.relation.ispartof	Complex, Intelligent, and Software Intensive Systems
dc.relation.ispartof	International Conference on Complex, Intelligent, and Software Intensive Systems
dc.relation.ispartofseries	Advances in Intelligent Systems and Computing
dc.relation.isbasedon	10.1007/978-3-030-22354-0_47
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Survey on Intelligent Chatbots: State-of-the-Art and Future Research Directions
dc.type	Conference Proceeding
utslib.citation.volume	993
utslib.location.activity	Sydney
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2021-05-05T06:09:13Z
pubs.finish-date	2019-07-05
pubs.place-of-publication	Switzerland
pubs.publication-status	Published
pubs.start-date	2019-07-03
pubs.volume	993
dc.location	Switzerland

Abstract:

Human-computer interaction (HCI) is an area of interest which plays a major role in understanding the interaction between humans and machines. Dialogue systems or conversational systems including chatbots, voice control interfaces and personal assistants are examples of HCI application that have been developed to interact with users using natural language. Chatbots can help customers find useful information for their needs. Thus, numerous organizations are using chatbots to automate their customer service. Thus, the needs for using artificial intelligence has been increasing due to the needs of automated services. However, devolving smart bots that can respond at the human level is challenging. In this paper, we survey the state-of-art chatbot approaches from based on the ability to generate appropriate responses perspective. After summarizing the review from this aspect, we identify the research issues and challenges in chatbots. The findings of this research will highlight directions for future work.

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http://hdl.handle.net/10453/148713