PRIVACY ANALYSIS OF COMMENT USING TEXT MINING IN OSN FRAMEWORK

Priya. M, Rengamani B, Blessy Selvam

Abstract


The most interactive medium in today’s world is the Online Social Network(OSN) that are used to communicate, share and disseminate information considerable amount of human life information. Stretch out the work to execute data separating way to deal with be utilized to enable clients to naturally screen the messages composed without anyone else dividers, by sifting through undesirable messages and remarks about pictures. The point of the present work is outline structure, called Filtered Wall (FW), ready to channel undesirable messages from OSN client dividers. At that point misuse machine Learning (ML) way to deal with actualize content mining methods to naturally appoint with each short instant message an arrangement of classifications in light of its substance. The most critical exertion is to actualize short content classifier (STC) is accustomed to separating and choosing the tokens from remarks. At that point utilizing sifted guidelines and piece list ways to deal with takeout undesirable messages and furthermore obstruct the companions who are send the undesirable messages ceaselessly and they are naturally separated by server. This idea can be actualized continuously to send versatile implication at the season of client in disconnected mode about negative remarks and also block the friends who has send the negative message continously. So client can undoubtedly monitor the framework from protection infringement.

Keywords


Short text classification, Filtered rules, Text mining , Blocked list, Tokenization

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DOI: https://doi.org/10.26483/ijarcs.v9i2.5765

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