A multi-agent conversational system with heterogeneous data sources access
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ArticleDate
2016-01-28Online Publication Date
2016-01-28Print Publication Date
2016-07Permanent link to this record
http://hdl.handle.net/10754/595321
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In many of the problems that can be found nowadays, information is scattered across different heterogeneous data sources. Most of the natural language interfaces just focus on a very specific part of the problem (e.g. an interface to a relational database, or an interface to an ontology). However, from the point of view of users, it does not matter where the information is stored, they just want to get the knowledge in an integrated, transparent, efficient, effective, and pleasant way. To solve this problem, this article proposes a generic multi-agent conversational architecture that follows the divide and conquer philosophy and considers two different types of agents. Expert agents are specialized in accessing different knowledge sources, and decision agents coordinate them to provide a coherent final answer to the user. This architecture has been used to design and implement SmartSeller, a specific system which includes a Virtual Assistant to answer general questions and a Bookseller to query a book database. A deep analysis regarding other relevant systems has demonstrated that our proposal provides several improvements at some key features presented along the paper.Citation
A multi-agent conversational system with heterogeneous data sources access 2016 Expert Systems with ApplicationsPublisher
Elsevier BVJournal
Expert Systems with ApplicationsAdditional Links
http://linkinghub.elsevier.com/retrieve/pii/S0957417416000567ae974a485f413a2113503eed53cd6c53
10.1016/j.eswa.2016.01.033