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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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2. Lu Z: PubMed and beyond: a survey of web tools for searching biomedical literature. Database (Oxford); 2011;2011:baq036
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  • [Source] The source of this record is MEDLINE®, a database of the U.S. National Library of Medicine.
  • [Title] PubMed and beyond: a survey of web tools for searching biomedical literature.
  • The past decade has witnessed the modern advances of high-throughput technology and rapid growth of research capacity in producing large-scale biological data, both of which were concomitant with an exponential growth of biomedical literature.
  • This wealth of scholarly knowledge is of significant importance for researchers in making scientific discoveries and healthcare professionals in managing health-related matters.
  • However, the acquisition of such information is becoming increasingly difficult due to its large volume and rapid growth.
  • In response, the National Center for Biotechnology Information (NCBI) is continuously making changes to its PubMed Web service for improvement.
  • Meanwhile, different entities have devoted themselves to developing Web tools for helping users quickly and efficiently search and retrieve relevant publications.
  • These practices, together with maturity in the field of text mining, have led to an increase in the number and quality of various Web tools that provide comparable literature search service to PubMed.
  • In this study, we review 28 such tools, highlight their respective innovations, compare them to the PubMed system and one another, and discuss directions for future development.
  • Furthermore, we have built a website dedicated to tracking existing systems and future advances in the field of biomedical literature search.
  • Taken together, our work serves information seekers in choosing tools for their needs and service providers and developers in keeping current in the field.
  • Database URL: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/search.

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  • (PMID = 21245076.001).
  • [ISSN] 1758-0463
  • [Journal-full-title] Database : the journal of biological databases and curation
  • [ISO-abbreviation] Database (Oxford)
  • [Language] ENG
  • [Grant] United States / Intramural NIH HHS / /
  • [Publication-type] Journal Article; Research Support, N.I.H., Intramural; Review
  • [Publication-country] England
  • [Other-IDs] NLM/ PMC3025693
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