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1. Yoo S, Choi J: Evaluation of Term Ranking Algorithms for Pseudo-Relevance Feedback in MEDLINE Retrieval. Healthc Inform Res; 2011 Jun;17(2):120-30
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  • [Source] The source of this record is MEDLINE®, a database of the U.S. National Library of Medicine.
  • [Title] Evaluation of Term Ranking Algorithms for Pseudo-Relevance Feedback in MEDLINE Retrieval.
  • OBJECTIVES: The purpose of this study was to investigate the effects of query expansion algorithms for MEDLINE retrieval within a pseudo-relevance feedback framework.
  • METHODS: A number of query expansion algorithms were tested using various term ranking formulas, focusing on query expansion based on pseudo-relevance feedback.
  • The OHSUMED test collection, which is a subset of the MEDLINE database, was used as a test corpus.
  • Various ranking algorithms were tested in combination with different term re-weighting algorithms.
  • RESULTS: Our comprehensive evaluation showed that the local context analysis ranking algorithm, when used in combination with one of the reweighting algorithms - Rocchio, the probabilistic model, and our variants - significantly outperformed other algorithm combinations by up to 12% (paired t-test; p < 0.05).
  • In a pseudo-relevance feedback framework, effective query expansion would be achieved by the careful consideration of term ranking and re-weighting algorithm pairs, at least in the context of the OHSUMED corpus.
  • CONCLUSIONS: Comparative experiments on term ranking algorithms were performed in the context of a subset of MEDLINE documents.
  • With medical documents, local context analysis, which uses co-occurrence with all query terms, significantly outperformed various term ranking methods based on both frequency and distribution analyses.
  • Furthermore, the results of the experiments demonstrated that the term rank-based re-weighting method contributed to a remarkable improvement in mean average precision.

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  • (PMID = 21886873.001).
  • [ISSN] 2093-369X
  • [Journal-full-title] Healthcare informatics research
  • [ISO-abbreviation] Healthc Inform Res
  • [Language] eng
  • [Publication-type] Journal Article
  • [Publication-country] Korea (South)
  • [Other-IDs] NLM/ PMC3155169
  • [Keywords] NOTNLM ; Evaluation Studies / Information Storage and Retrieval / MEDLINE
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