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Social data mining is an interesting phenomenon which colligates different sources of social data to extract information. This information can be used in relationship prediction, decision making, pat-tern recognition, social mapping, responsibility distribution and many other applications. This paper presents a systematical data mining architecture to mine intellectual knowledge from social data. In this paper, the authors use social networking site facebook as primary data source. They collect different attributes such as about me, comments, wall post and age from facebook as raw data and use advanced data mining approaches to excavate intellectual knowledge. They also analyze their mined knowledge with comparison for possible usages like as human behavior prediction, pattern recognition, job responsibility distribution, decision making and product promoting.
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