
handle: 10281/56733 , 11386/4503257
The aim of this paper is to propose a novel query expansion method to improve accuracy of text retrieval systems. Our technique makes use of a minimal explicit relevance feedback to expand an initial query with a structured representation called Weighted Word Pairs. Such a structure can be automatically extracted from a set of documents and uses a method for term extraction based on the probabilistic Topic Model. Evaluation has been conducted on TREC-8 repository and the proposed approach has been compared with other baseline query expansion schemes; experiments confirmed that the proposed method obtain a better performance than the baseline.
Text Retrieval; Query Expansion; explicit relevance feedback; probabilistic relevance feedback, Explicit relevance feedback; Probabilistic topic model; Query expansion; Text retrieval; Software, Explicit relevance feedback; Probabilistic topic model; Query expansion; Text retrieval;
Text Retrieval; Query Expansion; explicit relevance feedback; probabilistic relevance feedback, Explicit relevance feedback; Probabilistic topic model; Query expansion; Text retrieval; Software, Explicit relevance feedback; Probabilistic topic model; Query expansion; Text retrieval;
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