Title: LMS: a Long-term knowledge-based Multimedia retrieval System for region-based image databases

Authors: Xin Chen, Chengcui Zhang, Shu-Ching Chen, Min Chen

Addresses: Department of Computer and Information Sciences, The University of Alabama at Birmingham, CH 127 1530 3rd Ave S, Birmingham, AL 35294, USA. ' Department of Computer and Information Sciences, The University of Alabama at Birmingham, CH 127 1530 3rd Ave S, Birmingham, AL 35294, USA. ' School of Computing and Information Sciences, Florida International University, Miami, FL 33199, USA. ' School of Computing and Information Sciences, Florida International University, Miami, FL 33199, USA

Abstract: The Content-Based Image Retrieval (CBIR) system is a special kind of knowledge-based multimedia retrieval system. Relevance Feedback (RF) is a widely used technique in CBIR for incorporating the user|s knowledge with the learning process, which has been shown to significantly increase the retrieval accuracy. However, the user preferences obtained through RF are often discarded at the end of search, thus requiring the feedback process to restart for each new query. This paper proposes a Long-term knowledge-based Multimedia retrieval System (LMS) based on Latent Semantic Indexing (LSI) and human interaction (RF). Experiments show the effectiveness of the proposed system.

Keywords: human interaction; multimedia retrieval systems; knowledge based systems; KBS; region-based image retrieval; latent semantic indexing; LSI; one-class support vector machine; SVM; relevance feedback; learning.

DOI: 10.1504/IJASS.2007.019304

International Journal of Applied Systemic Studies, 2007 Vol.1 No.4, pp.416 - 435

Available online: 06 Jul 2008 *

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