A Literature Survey of Recent Advances in Chatbots

Chatbots are intelligent conversational computer systems designed to mimic human conversation to enable automated online guidance and support. The increased benefits of chatbots led to their wide adoption by many industries in order to provide virtual assistance to customers. Chatbots utilise method...

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Veröffentlicht in:Information (Basel) Jg. 13; H. 1; S. 41
Hauptverfasser: Caldarini, Guendalina, Jaf, Sardar, McGarry, Kenneth
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.01.2022
MDPI
Schlagworte:
Algorithms
Artificial Intelligence
chatbot
Chatbots
ChatScript
Computer Science
Computers
conversational agents
conversational modelling
Deep learning
human-computer dialogue system
Human-Computer Interaction
Interactive computer systems
Knowledge
Language
Literature reviews
Machine learning
Natural language processing
social chatbots
Verbal communication
Los Angeles California
United States > US
conversational modelling
chatbot
embodied conversational agents
conversational agents
ChatScript
conversation systems
conversational entities
conversational system
social chatbots
human-computer dialogue system
ISSN:2078-2489, 2078-2489
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Beschreibung
Zusammenfassung:Chatbots are intelligent conversational computer systems designed to mimic human conversation to enable automated online guidance and support. The increased benefits of chatbots led to their wide adoption by many industries in order to provide virtual assistance to customers. Chatbots utilise methods and algorithms from two Artificial Intelligence domains: Natural Language Processing and Machine Learning. 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. We highlight the main challenges and limitations of current work and make recommendations for future research investigation.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2078-2489
2078-2489
DOI:10.3390/info13010041