Journal of Jilin University(Information Science Ed ›› 2015, Vol. 33 ›› Issue (1): 72-78.

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Supporting Multi-Aspected Concept Discovery for Exploratory Search

ZHANG Yina, GAO Keningb, ZHANG Bina   

  1. a. College of Information Science and Engineering; b. Computing Center, Northeastern University, Shenyang 110004, China
  • Received:2014-07-15 Online:2015-01-24 Published:2015-03-20

Abstract:

In order to help exploratory search users discover important and valuable concepts for domains, and understand aspects of the concepts and comprehensively understand the problem domains, based on a concept usage model, concept importance and how problem aspects affect concept importance are analyzed to attain a method supporting multiaspected concept discovery. Such a method considers mutual affects between concept importance and problem aspects of concepts, leading to a simultaneous analysis on the two factors. Experimental results show that the proposed method could reduce search interactions by 48.8% and could improve concept occurrences by 24.3%.

Key words: exploratory search, concept discovery, rank cluster, concept importance

CLC Number: 

  • TP391