10. Automatic Query Expansion with Keyphrases and POS Phrase Categorization for Effective Biomedical Text Mining

  1. Xiaohua Hu2 and
  2. Yi Pan3
  1. Min Song1 and
  2. Il-Yeol Song2

Published Online: 23 MAY 2007

DOI: 10.1002/9780470124642.ch10

Knowledge Discovery in Bioinformatics: Techniques, Methods, and Applications

Knowledge Discovery in Bioinformatics: Techniques, Methods, and Applications

How to Cite

Song, M. and Song, I.-Y. (2007) Automatic Query Expansion with Keyphrases and POS Phrase Categorization for Effective Biomedical Text Mining, in Knowledge Discovery in Bioinformatics: Techniques, Methods, and Applications (eds X. Hu and Y. Pan), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470124642.ch10

Editor Information

  1. 2

    College of Information Science and Technology, Drexel University, Philadelphia, PA 19104, USA

  2. 3

    Department of Computer Science, Georgia State University, Atlanta, GA 30302-4110, USA

Author Information

  1. 1

    Department of Information System, College of Computing Sciences, New Jersey Institute of Technology, Newark, NJ 07102-1982, USA

  2. 2

    College of Information Science and Technology, Drexel University, Philadelphia, PA 19104, USA

Publication History

  1. Published Online: 23 MAY 2007
  2. Published Print: 25 MAY 2007

ISBN Information

Print ISBN: 9780471777960

Online ISBN: 9780470124642

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Keywords:

  • automatic query expansion with keyphrases and POS phrase;
  • keyphrase extraction-based pseudo-relevance feedback;
  • Medline with four query expansion algorithms

Summary

This chapter contains sections titled:

  • Keyphrase Extraction-Based Pseudo-Relevance Feedback

  • Query Expansion with WordNet

  • Experiments on Medline Data Sets

  • Conclusions

  • References