A Survey on Filtering Unwanted Messages from Online Social Network Users Wall Using Text Classification
|Akshay Bagal , Shriniwas Gadage
P.G.Student, Dept. of Computer Engineering, G.H.R.C.E.M Pune, Savitribai Phule Pune University, India
Professor, Dept. of Computer Engineering, G.H.R.C.E.M Pune, Savitribai Phule Pune University, India.
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Today one of the best communication between people is using the Online social network to which they can share information. Therefore the users who are using Online Social Networks(OSN) requires control over the unwanted messages that are posted on thier walls and to avoid the unwanted content which is displayed on private space of user. OSN provide us little support to the users requirement. To provide this, we propose a system which allows OSN users to have a direct control on the messages posted on users walls. This is achieved through a flexible rule based system in which users to customize the filtering criteria to be applied to their walls, and a Machine Learning (ML) based soft classification and short text classification which automatically produce membership labels in support of content-based filtering of a unwanted messages.