A logic-based approach for adaptive information filtering agents

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review

2 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
PublisherSpringer Verlag
Pages269-278
Volume2112
ISBN (Print)3540425977, 9783540454083
Publication statusPublished - 2001
Externally publishedYes

Publication series

Name
Volume2112
ISSN (Print)0302-9743

Conference

Title6th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2000
PlaceAustralia
CityMelbourne
Period28 August - 1 September 2000

Abstract

Adaptive information filtering agents have been developed to alleviate the problem of information overload on the Internet. However, the explanatory power and the learning autonomy of these agents can be improved. Applying a logic-based framework for representation, learning, and matching in adaptive information filtering agents is promising since users' changing information needs can automatically be deduced by the agents. In addition, the inferred changes can be explained and justified based on formal deduction. This paper examines how the AGM belief revision logic can be applied to the learning processes of these agents.

Citation Format(s)

A logic-based approach for adaptive information filtering agents. / Lau, Raymond; Hofstede, Arthur H.M. Ter; Bruza, Peter D.
Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). Vol. 2112 Springer Verlag, 2001. p. 269-278.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review