REDUCING ATTRIBUTES of FACEBOOK USERS USING ROUGH SET THEORY | ||||
| International Journal of Intelligent Computing and Information Sciences | ||||
| Article 3, Volume 16, Issue 4, October 2016, Page 29-40 PDF (2.47 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/ijicis.2016.19824 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| W. Abdallah1; S. Sarhan1; Samir Elmougy2 | ||||
| 1Dept. of Computer Science, Faculty of Computers and Information, Mansoura University, Mansoura 35516, Egypt. | ||||
| 2Dept. of Computer Science, Faculty of Computers and Information, Mansoura University, Mansoura 35516, Egypt | ||||
| Abstract | ||||
| Using social networks have become one of the daily activities that billions of peoples around the world do. So, great research efforts had been done to analyze and understand these virtual communities. Among other things, link prediction is a paramount task to analyze and understand these social networks. In this paper, we investigate link prediction problem using rough set theory to discard the irrelevant attributes that could be found in the profiles of Facebook users and the proposed work induces accuracy 97.79%. | ||||
| Keywords | ||||
| Link Prediction; Social networks; Rough set theory; facebook; Self-Organization Map | ||||
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