Filteration of Unwanted Text Messages From Online Social Networks Using Probabilisitc Classifier
Journal Title: Scholars Journal of Engineering and Technology - Year 2017, Vol 5, Issue 8
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. Keywords: Filtering System, Online Social Networks, Information Filtering, Clustering
Authors and Affiliations
Garima Singh, Amit Yerpude, Toran Verma
Keywords
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