Chatbots: History, technology, and applications
Чат-боты: история, технологии и приложения
2020-11-09
SCID: 54.1/9px9h922
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architectural designchatbotsmachine learningnatural dialog systemspattern matching
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Abstract (AI)
This literature review presents the History, Technology, and Applications of Natural Dialog Systems or simply chatbots. It aims to organize critical information that is a necessary background for further research activity in the field of chatbots. More specifically, while giving the historical evolution, from the generative idea to the present day, we point out possible weaknesses of each stage. After we present a complete categorization system, we analyze the two essential implementation technologies, namely, the pattern matching approach and machine learning. Moreover, we compose a general architectural design that gathers critical details, and we highlight crucial issues to take into account before system design. Furthermore, we present chatbots applications and industrial use cases while we point out the risks of using chatbots and suggest ways to mitigate them. Finally, we conclude by stating our view regarding the direction of technology so that chatbots will become really smart.
Key Findings
1
A complete categorization system for chatbots is presented to organize critical background information for future research.
2
A general architectural design is proposed that aggregates critical design details and highlights crucial pre-design considerations.
3
Chatbot applications and industrial use cases are surveyed, along with risks of chatbot deployment and suggested mitigation strategies.
4
The authors state a perspective on future directions so that chatbots can become 'really smart'.
5
The paper provides a historical evolution of chatbots from early generative ideas to modern systems, identifying weaknesses at each stage.
6
Two essential implementation technologies are analyzed in detail: pattern matching approaches and machine learning.
Research Object
Chatbots (Natural Dialog Systems)
Research Subject
Their history, implementation technologies (pattern-matching and machine-learning approaches), architectures, applications, risks, and design-related issues
Publication Details
Publication Date
2020-11-09
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