Social networking services are used for communication between people to share information through internet. The unbounded growth of content and users pushes the internet technologies to certain limitations. Data mining plays a major role in the field of social network to extract relevant content from the voluminous data which is being a phenomenal task, because of its dynamic nature the participation is more complex. The major problem, users face spammer's interaction which leads to misunderstanding and inconvenience for social activities. This work concentrates on detecting the spammer actions using feature relevance analysis and applying efficient classifier. The main objective of the proposed work is to find relationship between features and classifying patterns for detecting spam message from the unwanted sites. The system applies efficient classification algorithms after feature relevance analysis for detecting spam in better way. The outcome of this project will serve for the users participating in social networks for effective purpose like business, marketing and establishing contacts.
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