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Survey Paper | Computer Science & Engineering | India | Volume 3 Issue 11, November 2014 | Rating: 6.2 / 10
The Survey Paper on Filter Unwanted Messages from Walls and Blocking Non-legitimate Users in OSN
Pallavi Shinde, Trupti Gedam
Abstract: In recent years, Online Social Networks (OSNs) have become an vital part of daily life. Users build specific networks to represent their social relationships. Users can upload and share information associated to their personal lives. The privacy risks of such behavior are often ignored. And the basic issue in today On-line Social Networks is to give users the ability to control the messages posted on their own private space to avoid that unwanted content is displayed. Today OSNs provide very little or no support to prevent unwanted messages on user walls. For that purpose, we proposed a new system allowing OSN users to have a direct control on the messages posted on their walls. This is achieved through a flexible rule-based system, that permits users to customize the filtering criteria to be applied to their walls, and a Machine Learning (ML) based soft classifier automatically labeling messages in support of content-based filtering. The system utilizes a ML soft classifier to enforce customizable content-dependent Filtering Rules. And the flexibility of the system in terms of filtering options is enhanced through the management of Blacklists. The proposed system gives security to the On-line Social Networks.
Keywords: Online social network, content based filtering, filtering rules, machine learning, policy based personlization
Edition: Volume 3 Issue 11, November 2014,
Pages: 2816 - 2818