• DocumentCode
    478055
  • Title

    The New Clustering Strategy and Algorithm Based on Latent Semantic Indexing

  • Author

    Yan, Bing ; Du, Yajun ; Li, ZhanShen

  • Author_Institution
    Sch. of Math. & Comput. Sci., Xihua Univ., Chengdu
  • Volume
    1
  • fYear
    2008
  • fDate
    18-20 Oct. 2008
  • Firstpage
    486
  • Lastpage
    490
  • Abstract
    Currently, the technology of search engine is a hot in IR research. Clustering according to the themes of the search results will be well to help user to find the information. In this paper, the new clustering algorithm, which named MyCluster and based on the phrase and latent semantic indexing, is proposed. The result of MyCluster is composed of class labels and class contents. The class contents is a entry for users getting the information. Each class label corresponding to some class contents. The readability of cluster labels will effect the efficiency of finding a useful information. We adopt a method of singular value decomposition to induce class labels and find class contents, so that the clusters have the characteristic that objects belonging to the same cluster are "similar", while objects from different clusters are "dissimilar". Lastly, we incorporate and sort the clusters. By experiments, our MyCluster has some advantages of the readability of class labels and the relevance of class contents.
  • Keywords
    indexing; information retrieval; search engines; MyCluster; class contents; class label; clustering algorithm; information retrieval; latent semantic indexing; search engine; singular value decomposition; Clustering algorithms; Computer science; Indexing; Information retrieval; Mathematics; Optical computing; Optical scattering; Search engines; Web pages; Web search; Clustering Strategy; Latent Semantic Indexing; class contents; class label;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2008. ICNC '08. Fourth International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-0-7695-3304-9
  • Type

    conf

  • DOI
    10.1109/ICNC.2008.699
  • Filename
    4666894