A System to Filter Unwanted Messages from OSN User Walls using Trustworthiness

The core problem in todays Online Social Networks (OSNs) is to allocate users the authority to manage the messages posted on their private space to avert that unwanted content. The unwanted data may contains political, vulgar, non neural etc. message filtering systems are designed for unstructured or semi-structured data, as opposed to database applications, which use very structured data. In this paper we proposed a System with the flexible rules to filter the unwanted messages posted on user wall. After crossing threshold value the notification message is send to that user. This allows users to customize the refining criteria to be applied to their walls, and a Machine Learning-based classifier automatically classify the messages and labelling messages in support of content-based filtering.