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Filtering Noisy Contents in Online Social Network by using Rule Based Filtering System

Bala Kumari P, Bercelin Rose Mary W and Devi Mareeswari M

The aim of the present work is to propose and experimentally evaluate an automated system, called Filtered Wall (FW), able to filter noisy messages from OSN user space. In Online Social Network may has possibilities of posting some noisy contents so it need to filter without displaying to owner space. It has achieved by using Rule based System. The Rule Based System allows users customize to filter by applying Filtering Criteria. This work exploits Machine Learning (ML) text categorization techniques to automatically assign with each short text message a set of categories based on its content. Online social networks not only make it easier for users to share their opinions with each other, but also serve as a platform for developing new filter algorithms.