• DocumentCode
    3453705
  • Title

    A Document Clustering Technique Based on Term Clustering and Association Rules

  • Author

    Cheng, Yuepeng ; Li, Tong ; Zhu, Song

  • Author_Institution
    Comput. Sci. & Eng. Dept., North China Inst. of Aerosp. Eng., Langfang, China
  • fYear
    2010
  • fDate
    27-28 Nov. 2010
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    With development of internet and database technology, web mining has got more and more attentions from information science domain. This paper proposes a document clustering technique based on term clustering and association rules. In this technique, extract words from document collection firstly, then construct term clustering according to AMI(Average Mutual Information) between terms, document VSM(Vector Space Model) is represented by term clustering, and use association rules to mine document clustering. Experiment results show that performance and clustering quality of this technique are improved than those of traditional methods in the clustering process.
  • Keywords
    data mining; pattern clustering; vectors; word processing; Web mining; association rule; average mutual information; document clustering technique; term clustering; vector space model; word extraction; Aerospace engineering; Association rules; Clustering algorithms; Mutual information; Semantics; Variable speed drives; Web mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Database Technology and Applications (DBTA), 2010 2nd International Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-6975-8
  • Electronic_ISBN
    978-1-4244-6977-2
  • Type

    conf

  • DOI
    10.1109/DBTA.2010.5659049
  • Filename
    5659049