Context Based Text Document Sharing System Using Association Rule Mining

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.