Machine Learning techniques for filtering of unwanted messages in Online Social Networks
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2016, Vol 18, Issue 3
Abstract
As of Recent Years, Online Social Networks have transformed into a key bit of step by step life. One key issue in today user wall(s) is to give users the ability to control the messages posted in solitude private space to keep up a vital separation from that undesirable substance is appeared. Up to now userwalls give small support to this need. To fill the fissure, I propose a structure allowing user divider users to have a prompt control on the messages posted on their walls. This is refined through a versatile principle based structure, thatallows users to change the filtering criteria to be associated with their walls, and Machine Learning based sensitive classifier actually checking messages in moving of substance based isolating. T-OSN expect a urgent part in regular life. User can relate with other user by sharing a couple sorts of substance such as picture, sound and video substance. Main problem in OSN (Online Social Network) is to hindering security in posting undesirable messages. Ability to have a prompt control over the messages posted on user divider is not gave.Undesirable post will be particularly posted on general society divider. Simply the undesirable messages will be blocked not the user. To keep up a vital separation from this issue, BL (Black List) part is proposed in thispaper, which avoid undesired producers messages. BL is used to make sense of which user should be inserted in BL and pick when the support of the user is finished. Machine Learning Text Categorization is in like mannerused to arrange the short texts.
Authors and Affiliations
Pinniboyina Venkateswarlu , R Lakshmi Tulasi
Keywords
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