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
Link To Document :
بازگشت