Title :
Intellectual knowledge extraction from online social data
Author :
Rahman, Muhammad Mahbubur
Author_Institution :
Dept. of Comput. Sci., American Int. Univ.- Bangladesh, Dhaka, Bangladesh
Abstract :
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, pattern 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 research, we use social networking site facebook as primary data source. We 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. We also analyze our mined knowledge with comparison for possible usages like as human behavior prediction, pattern recognition, job responsibility distribution, decision making and product promoting.
Keywords :
data mining; decision making; social networking (online); Facebook; decision making; human behavior prediction; information extraction; intellectual knowledge extraction; intellectual knowledge mining; job responsibility distribution; online social data mining; pattern recognition; product promotion; relationship prediction; responsibility distribution; social mapping; social networking site; systematical data mining architecture; Facebook; Ice; Visualization; Data Mining; Facebook; Intellectual Knowledge; Social Computing;
Conference_Titel :
Informatics, Electronics & Vision (ICIEV), 2012 International Conference on
Conference_Location :
Dhaka
Print_ISBN :
978-1-4673-1153-3
DOI :
10.1109/ICIEV.2012.6317392