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Title page for ETD etd-12032008-215608

Type of Document Dissertation
Author Fu, Lawrence Dachen
Author's Email Address lawrence.fu@vanderbilt.edu
URN etd-12032008-215608
Title Improving Biomedical Information Retrieval Citation Metrics Using Machine Learning
Degree PhD
Department Biomedical Informatics
Advisory Committee
Advisor Name Title
Constantin Aliferis Committee Chair
Cynthia Gadd Committee Member
Daniel Masys Committee Member
Lily Wang Committee Member
Nunzia Giuse Committee Member
  • information retrieval
  • machine learning
  • citation metrics
  • scientometrics
Date of Defense 2008-09-05
Availability unrestricted
The evaluation of the literature is an increasingly integral part of biomedical research. Clinicians, researchers, librarians, and others routinely use the literature to answer questions for clinical care and research. The size of the literature prevents the manual review of all documents, and automated methods are necessary for identifying high quality articles as a major filtering step. This work aimed to improve the performance and usability of existing tools with machine learning methods. First, evaluation methods for journals, articles, and websites were studied to determine if their performance varied widely for different topics. Second, the feasibility of predicting article citation count was examined by training Support Vector Machine (SVM) models on content and bibliometric features. Third, SVM models were used to automatically classify instrumental and non-instrumental citations.
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