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  Filtered Wall Architecture for Social Networks  
  Authors : Seema Kanhaiya; Tejal Jadhav; Ankita Patil; Shilpa Birajdar
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The basic problem in today’s On-line Social Networks (OSNs) is to give users the ability to control the messages posted on their own private space to avoid that unwanted content is displayed. Up to now social networks provide little support to this requirement. So in this paper, we propose a system allowing OSN users to have a direct control on the messages posted on their walls. We are using here a flexible rule-based system, that allows users to customize the filtering criteria to be applied to their walls, and a Machine Learning based soft classifier automatically labeling messages in support of content-based filtering.

 

Published In : IJCSN Journal Volume 4, Issue 2

Date of Publication : April 2015

Pages : 405 - 408

Figures : 01

Tables : --

Publication Link : Filtered Wall Architecture for Social Networks

 

 

 

Seema Kanhaiya : G.H.Raisoni Institute of Engineering & Technology, Pune Savitribai Phule University of Pune, Dist-Pune, State-Maharashtra, India. Zip-412207

Tejal Jadhav : G.H.Raisoni Institute of Engineering & Technology, Pune Savitribai Phule University of Pune, Dist-Pune, State-Maharashtra, India. Zip-412207

Ankita Patil : G.H.Raisoni Institute of Engineering & Technology, Pune Savitribai Phule University of Pune, Dist-Pune, State-Maharashtra, India. Zip-412207

Shilpa Birajdar : G.H.Raisoni Institute of Engineering & Technology, Pune Savitribai Phule University of Pune, Dist-Pune, State-Maharashtra, India. Zip-412207

 

 

 

 

 

 

 

On-line Social Networks

Filtered Wall

Machine Learning

Short Text Classifier

In this paper, we have presented a system to filter undesired messages from OSN walls. The system develops a ML soft classifier to implement customizable content-dependent FRs. In particular, we aim at investigating a tool able to automatically recommend trust values for those contacts user does not individually identified. We do consider that such a tool should propose expectation assessment based on users procedures, performances, and reputation in OSN, which might involve enhancing OSN with assessment methods. Though, the propose of these assessment based tools is difficult by several concern s, like the suggestions an assessment system might have on users’ confidentiality and/or the restrictions on what it is possible to audit in present OSNs. An introduction work in this direction has been prepared in the context of expectation values used for OSN access control purposes. We would like to remark that the system proposed in this paper represents just the core set of functionalities needed to provide a sophisticated tool for OSN message filtering. Still if we have balanced our system with an online associate to set FR thresholds, the improvement of an absolute system effortlessly exploitable by average OSN users is a wide topic which is out of the scope of the present paper.

 

 

 

 

 

 

 

 

 

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