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Dynamic Construction of Category Hierarchy Using Fuzzy Relational Products

  • Bumghi Choi
  • Ju-Hong Lee
  • Sun Park
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2690)

Abstract

Overwhelming search results often daunt web surfers on the web search engine. There have been many systems to try to solve this problem by constructing more specific search methods. Auto categorization and clustering have been presented. However, an efficient way of constructing the hierarchy of generated or pre-existing categories has not been suggested. We provide a dynamic category hierarchy structuring algorithm to reinforce the categorization and the clustering with using the fuzzy relational products. In this paper, we also propose a novel search method using this algorithm to complement the conventional directory search or category browsing and enhance the efficiency of search. Results from our evaluation show that our method helps users find categories more quickly and easily than conventional directory searching methods.

Keywords

Membership Degree Fuzzy Subset Latent Semantic Indexing Category Hierarchy Dynamic Construction 
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-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Bumghi Choi
    • 1
  • Ju-Hong Lee
    • 2
  • Sun Park
    • 2
  1. 1.Quark Co., Ltd.SeoulKorea
  2. 2.School of Computer Science and EngineeringInha UniversityIncheonKorea

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