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Fuzzy Keywords Query

  • Shanshan Han
  • Hongzhi WangEmail author
  • Hong Gao
  • Jianzhong Li
  • Shenbin Huang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9932)

Abstract

Considering advantages and disadvantages of search engines and SQL query of keywords search, we propose a novel method of constructing fuzzy ontology model combining ontology with fuzzy sets. We introduce membership functions and the fuzzy operator, then expand semantic keywords based on the semantic synonym dictionary. To process query effectively, we design an optimized storage structure based on B* tree. Some techniques, such as index mechanism, are used in our system. Based on these techniques, we propose a top-k query which uses dynamic filtering to accelerate processes. We experimentally demonstrate the accuracy and efficiency of the methods.

Keywords

Membership Function Semantic Similarity Query Result Semantic Distance Keyword Query 
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.

Notes

Acknowledgments

This paper was partially supported by National Sci-Tech Support Plan 2015BAH10F01 and NSFC grant U1509216,61472099,61133002 and the Scientific Research Foundation for the Returned Overseas Chinese Scholars of Heilongjiang Province LC2016026.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Shanshan Han
    • 1
  • Hongzhi Wang
    • 1
    Email author
  • Hong Gao
    • 1
  • Jianzhong Li
    • 1
  • Shenbin Huang
    • 1
  1. 1.Harbin Institute of TechnologyHarbinChina

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