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In this paper, our focus is to capture the limitations of Pseudo-Relevance Feedback (PRF) based query expansion (QE) and propose a hybrid method to improve the performance of PRF-based QE by combining corpus-based term co-occurrence information, context window of query terms and semantic information of term.
Effective Query Expansion with the Resistance Distance Based Term Similarity Metric Shuguang Wang Intelligent Systems Program University of Pittsburgh Pittsburgh, PA In this paper, we will discuss how to build the metric where Q is a query, x is a term, and X is the set of all terms.
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