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    Scholars Journal of Engineering and Technology | Volume-5 | Issue-08
        Filteration of Unwanted Text Messages From Online Social Networks Using Probabilisitc Classifier
        Garima Singh, Prof. Amit Yerpude, Prof. Toran Verma
        
            Published:  Aug. 30, 2017 | 
             294
             375
        
        DOI:  10.21276/sjet
        Pages:  447-451
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        Abstract
        Now-a-days, Online Social Networking sites are important part of human society. In other way a person
maintains a social networking site account which is then used for the following purposes like building relations, for
business, exchange of data etc. The use of OSN’s is therefore tremendously increasing day by day and its demanding for
concentration over protection of private information of user’s, their likes and dislikes etc. There are different filtering
criteria’s provided by various OSN’s but the role of user to prevent his/her privacy is very less with the help of those
criteria’s. This paper represents a model that helps to allow the user to take over the control of their profile’s and walls.
The key parameters of the proposal illustrate are that the message posted on user wall’s will be filtered for unwanted
content in any form and type and will be posted with the users consent only. The feasibility of this model is presented
considering OSN’s scenarios.
    

