Filtered Wall: An Automated System to Filter Unwanted Messages from OSN User Profiles
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2014, Vol 3, Issue 9
Abstract
In recent years, Online Social Networks (OSNs) have become an important part of daily life. Users build explicit networks to represent their social relationships. Users can upload and share information related to their personal lives. The potential privacy risks of such behavior are often ignored. And the fundamental 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 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 allows 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 exploits a ML soft classifier to enforce customizable contentdependent 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.
Authors and Affiliations
Pechetti Santosh, R. Praveen kumar
Keywords
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- EP ID EP28017
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