Discovering Relevant Concepts for Web Image Search

Abstract

It is difficult for users to browse the images retrieved from conventional Web search engines. The paper presents an approach that organizes the retrieved images with auto-generated relevant concepts to users’ queries. The proposed approach is a well-integrated set of techniques, including relevant concept finding, query clustering, and query classification. The experimental results show that the performance of Web image retrieval can be effectively improved with the proposed approach.