FUHM: A System to Filter Undesired Hindi Messages from OSN Users Wall
Online Social Networks (OSN) are popularly used for sharing data, information or knowledge among the people
having similar interests. Todays OSN like, Facebook classifies the messages based on sender’s relationship with the receiver.
The challenge is to give OSN users the ability to filter a message posted on their own private space based on its content, like
blocking a political message. In this paper, we propose Filtering Undesired Hindi Messages (FUHM) Algorithm that allows
users to define their own filtering criteria for messages posted on their wall. This is attained by a rule based system and a text
classifier. Time taken in classification process adds to the efficiency of overall system. Proposed algorithm is time efficient
as compare to previously available methods as we use multiclass classification, classifying mes-sage into different categories
in one step.
Keywords - Content Based Filtering, Message Filtering, Naive Baye’s Classifier, Online Social Network, Text Classi-