Knowledge Discovery in Textual Databases: A Concept-Association Mining Approach

  • Mutlu Mete
  • Nurcan Yuruk
  • Xiaowei Xu
  • Daniel Berleant
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 132)


The number of scientific publications is exploding as online digital libraries and the World Wide Web grow. MEDLINE, the premier bibliographic database of the National Library of Medicine (NLM) , contains about 18 million records from more than 7,300 different publications dating from 1965; it is growing by about 400,000 citations each year. The explosive growth of information in textual documents creates great need for techniques for knowledge discovery from text collections.


Association Rule Rule Mining Association Rule Mining Spread Cortical Depression Support Threshold 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Mutlu Mete
    • 1
  • Nurcan Yuruk
    • 2
  • Xiaowei Xu
    • 3
  • Daniel Berleant
    • 2
  1. 1.Department of Computer ScienceTexas A&M University-commerceCommerceUSA
  2. 2.Department of Applied ScienceUniversity of Arkansas at Little RockLittle RockUSA
  3. 3.Department of Information ScienceUniversity of Arkansas at Little RockLittle RockUSA

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