A PROBABILISTIC APPROACH TO METADATA FILTER IN SOCIAL NETWORK
Abstract
The proposed application model for
meta data keyword filter is a technique to monitor the user activities in social networks such as facebook and forum. The application has a background watcher which has the set of keywords added by the admin. The admin can add the list of crude or unkind words. When the user post a message the background watcher monitors the post and checks whether any crude or unkind word is in the message. If any appropriate content is deducted the message is banned by the background wall filter. The proposed approach is very accurate and efficient improving upon existing methods in terms of accuracy and efficiency in different settings. The application raises a warning message to the user who forward the unkind words to some other. If the user continues such behavior the respective user is blocked permanently
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