http://dx.doi.org/10.1504/IJAIP.2009.026763">
 

Document Type

Journal Article

Department/Unit

Department of Computer Science

Title

Community adaptive search engines

Language

English

Abstract

This paper introduces Community Adaptive Search Engines (CASE) for multimedia object retrieval. CASE systems adapt their behaviour depending on the collective feedback of the users in order to eventually converge to the optimal answer. The community adaptive approach uses continuous user feedbacks on the lists of returned objects in order to filter out irrelevant objects and promote the relevant ones. An original dealer/opponent game model for CASE is proposed and an evolutionary approach to solve the CASE game is also presented. Experimental results shows convergence to the optimal solution with acceptable performance for real domain sizes. Copyright © 2009 Inderscience Enterprises Ltd.

Keywords

Adaptive information retrieval, Collective knowledge, Evolutionary computation, Game theory

Publication Date

2009

Source Publication Title

International Journal of Advanced Intelligence Paradigms

Volume

1

Issue

4

Start Page

432

End Page

443

Publisher

Inderscience

ISSN (print)

17550386

ISSN (electronic)

17550394

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