Paper Title
Online Social Network Wall Filtering Using Ml And Human Sensing

Abstract
With the large amount of growth in the data and use of social networking sites users share free text, image, audio and video data daily. Today’s OSNs (Online Social Network System) not provide much support to the users to avoid unwanted messages displayed on their own their wall. In existing system, if unwanted words are found, system directly blocks the message. But the problem is important articles which include unwanted words but having positive or good topics, gets blocked. So, to overcome the above problem, we proposed a system in which data will be divided into three categories: Normal, Low risk and High risk. Then filtering rules are applied to block corresponding data using human intervention. Keywords- Machine Learning Techniques (MLT), Filtering Rules, SVM, Online Social Network.