A Frame Work for Filtering Unwanted Messages from OSN User Walls

Abstract

The user’s can communicate and share their views and content through online social networking services (OSN). The sharing between the users should be several types of content like image, audio, video etc.. In recent years online social networks (OSN) also increased rapidly. Online Social Networks (OSNs) are one of the most wanted and popular social networks where users can share, exchange and communicate with the large amount of information to each other. One basic issue in these OSNs is to give users a protected private space from the undesirable and unwanted messages displayed. So the main goal of the present work is to propose and experimentally evaluate Filtered Wall (FW) which is an automated system can filter noisy messages from OSN user space. This is possible through a flexible rule-based system that allows users to customize the filtering options to be used to their surfaces and a Machine Learning (ML) depended soft classifier involuntarily labeling messages in support of content-based filtering.