Similarity score for information filtering thresholds in business processes

Jun Lai, Ben Son, Saqib Ali

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


The tremendous growth in the amount of information available poses some key challenges for information filtering and retrieval. Users not only expect high quality and relevant information, but also wish that the information be presented in an as efficient way as possible. The traditional filtering methods, however, only consider the relevant values of document. These conventional methods fail to consider the efficiency of documents retrieval. In this paper, we propose a new algorithm to calculate pn index called document similarity score based on elements of the document. Using the index, document profile will be derived. Any documents with the similarity score above a given threshold wilt be clustered. Using these pre-clusiered documents, information filtering and retrieval can be made more efficient. Experimental results clearly show our proposed method tremendously improves the efficiency of information filtering and retrieval. We also give an example application of our proposed method in business processes.

Original languageEnglish
Title of host publicationProceedings of INMIC 2004 - 8th International Multitopic Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)0780386809, 9780780386808
Publication statusPublished - 2004
Externally publishedYes
Event8th International Multitopic Conference, INMIC 2004 - Lahore, Pakistan
Duration: Dec 24 2004Dec 26 2004

Publication series

NameProceedings of INMIC 2004 - 8th International Multitopic Conference


Other8th International Multitopic Conference, INMIC 2004


  • Business process
  • Clustering
  • Elements
  • Information filtering
  • Information retrieval
  • Search engine
  • Web crawlers
  • World Wide Web

ASJC Scopus subject areas

  • General Engineering
  • General Computer Science


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