MACHINE LEARNING CLASSIFICATION METHODS USED TO FILTER UNDESIRABLE MESSAGE FROM OSN USER WALLS

Computer Engineering

Now a day’s Social networking on social media websites involves the use of the internet to connect users with their friends, family and associates. The most well-known social media sites are Facebook, twitter, Instagram and LinkedIn. These sites allowed sharing photos, videos, and information, the main drawback of this On-line Social Networks (OSNs) is the lack of privacy for the user’s own private walls. This project represents system enforcing content-based message filtering consider as a key service for On-line Social Networks (OSNs). Our system provides ability to OSN users to possess a straight control on the messages denoted on their walls. Up to now, OSNs offer very little support to stop undesirable messages on user private walls, there is no content-based preferences are supported and so it's impossible to stop undesirable messages, like political or vulgar ones, regardless of the user who posts them. One basic issue during this system is blocking of user for lifetime. we tend to overcome this drawback by using proposed System; during this paper we tend to proposed a system that performs blocking of undesirable message user and additionally sends back a notification to it who has send undesirable message on user’s wall using threshold frequency worth. To filter messages we tend to proposed an increased filtering system by using machine learning based categorization techniques.

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