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Author(s):

Meghna Raghuwanshi , Prof Ram Meghe College of Technology And Research.; Dipika Siraskar, prmit&r,badnera; Monika Athavale, prmit&r,badnera; Prajakta Sukhdeve, prmit&r,badnera; Prof. Arpit Chaudhari, prmit&r,badnera

Keywords:

online social networks(OSN); posts; message filtering; pattern matching; filtered walls ;Machine Learning(ML) ;Filtering Rules(FR); Text Categorization, Filtering Rules(FW)

Abstract:

In the present day scenario online social networks (OSN) are very trendy and one of the most interactive medium to share, communicate and exchange different kinds of information like text, image, audio, video etc. The OSN users are provided with a privilege to have a direct control on posting or commenting certain stuff on their walls with the help of information filtering. This can be achieved through text pattern matching system, that allows the user to filter their open space (wall) and a privilege to add new words treated as unwanted. To provide a healthy environment to the user to interact, pattern matching of texts are done with the blacklisted vocabulary. If the posted content is verified as ethical and not spam , it is then allowed to be posted on someone’s wall, otherwise the posted text will be blurred or encoded with special symbols or would be placed into blacklisted words. This can be achieved through a flexible rule-based system, which allows the users to customize the refining criteria to be applied to their walls, and a Machine Learning-based classifier automatically classifies the messages in content-based filtering.


Other Details:

Manuscript Id :IJSTEV3I10200
Published in :Volume : 3, Issue : 10
Publication Date: 01/05/2017
Page(s): 427-431
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