Community Adaptive Search Engines. (26th June 2009)

• Record Type: Journal Article
• Authors: Milani, Alfredo; Leung, Clement; Chan, Alice
• Is Part Of: International journal of advanced intelligence paradigms. Volume 1:Number 4(2009)
• Page Start: 432
• Page End: 443
• Publication Date: 2009-06-26
• Subjects: adaptive information retrieval -- collective knowledge -- evolutionary computation -- game theory -- adaptive search engines -- multimedia object retrieval -- multimedia objects -- user feedback -- continuous feedback; Artificial intelligence -- Periodicals; Machine theory -- Periodicals; Fuzzy logic -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-0386

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.