• DocumentCode
    2697719
  • Title

    Extraction of keyterms by simple text mining for business information retrieval

  • Author

    Gao, Xiangzhu ; Murugesan, San ; Lo, Bruce

  • Author_Institution
    Southern Cross Univ., Lismore, NSW
  • fYear
    2005
  • fDate
    12-18 Oct. 2005
  • Firstpage
    332
  • Lastpage
    339
  • Abstract
    Much of business information is text and the information is subject to frequent changes. The use of efficient and effective mechanisms to retrieve required business information is a key to business success, and automated processing of text to extract key terms is an essential component of such an information retrieval (IR) system. Traditional text processing methods based on complex linguistic or statistic techniques are not efficient in dealing with frequently changing business information and do not necessarily provide satisfying IR results. We propose a simple method to extract important terms (keyterms) from text for application in different aspects of IR and show through experimentation that its performance is comparable to or better than complex methods
  • Keywords
    business data processing; data mining; indexing; information retrieval; text analysis; business information retrieval; keyterms extraction; linguistic technique; statistic technique; text mining; text processing; Data mining; Humans; Indexing; Information retrieval; Search engines; Text mining; Text processing; Thesauri; Vocabulary; Web pages;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    e-Business Engineering, 2005. ICEBE 2005. IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7695-2430-3
  • Type

    conf

  • DOI
    10.1109/ICEBE.2005.66
  • Filename
    1552912