Adaptive Query Expansion Based on Clustering Search Results

概要

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In this paper, we propose a new method of information retrieval which combines adaptive and incremental query expansion with cluster-based browsing. The proposed method attempts to accurately learn users' interests from their relevance judgments on clustered search results instead of individual documents, reducing users' loads for the judgments. The use of adaptive relevance feedback leads to the capability for tracking vague or dynamically shifting goals of users. Incrementally expanded and refined queries can be used in re-searching to improve the retrieval effectiveness. We present an application of the proposed method to the information retrieval on the World Wide Web and demonstrate its effectiveness through basic experiments.
一般社団法人情報処理学会の論文
1999-05-15