• DocumentCode
    255414
  • Title

    Context based text document sharing system using association rule mining

  • Author

    Dhande, K.A. ; Umale, J.S. ; Kulkarni, P.A.

  • Author_Institution
    Dept. of Comput. Eng., PCCOE, Pune, India
  • fYear
    2014
  • fDate
    11-13 Dec. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In today´s document sharing environment, when documents are shared over a group of people, document context of document and context of user is not considered. Therefore sometimes it may happen that the document may get delivered to unintended user over the network. This leads to unnecessary transfer of document. To reduce this document transfer overhead, we are proposing a system that will consider document context as well as user context. By using these both of the contexts, document will get transferred to only intend user. This will also reduce time overhead to transfer a document to a group of peoples, because users belong to different context than document context will be eliminated. To identify document context and user context, we proposed two models Constant Weight Distribution Model and Common Words Probability Model. We also proposed a context dictionary to store different contexts and associated terms with them.
  • Keywords
    data mining; probability; text analysis; association rule mining; common word probability model; constant weight distribution model; context dictionary; context-based text document sharing system; document transfer overhead reduction; time overhead reduction; user context; Association rules; Context; Context modeling; Dictionaries; History; Software; Software testing; Apriori Algorithm; Context; Context Dictionary; Document Context; Document Sharing; User Context;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    India Conference (INDICON), 2014 Annual IEEE
  • Conference_Location
    Pune
  • Print_ISBN
    978-1-4799-5362-2
  • Type

    conf

  • DOI
    10.1109/INDICON.2014.7030458
  • Filename
    7030458