Link Prediction in Social Network based on classifier fusion
Publish place: 3rd International Conference on Applied Research in Computer Engineering and Information Technology
Publish Year: 1394
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
CITCONF03_209
تاریخ نمایه سازی: 12 تیر 1395
Abstract:
Recently, Location-based Social Networks (LBSNs) have attracted millions of users, experiencing a hugepopularity increase over a short period of time. In Location-based social network, users can easily set their locations asa new interactive way to share with friends to inform them of their current location. Link prediction or predicting newcommunications is one of the fundamental and interesting problems in location-based social networks. In this paper, wepropose a new link predictor for LBSNs. In the proposed approach, the network is firstly partitioned into a number ofclusters. Then, a supervised link predictor is learnt for each cluster. To do this, we have used several learningalgorithms and compared their prediction accuracy to achieve the best performance. The results show that the proposedmethod obtains 97.77% accuracy
Keywords:
Link prediction , Location-based Social Networks (LBSNs)
Authors
Nasrin Torab
Dept. of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran
Hadi Shakibian
Dept. of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran
Nasrollah moghadam charkari
Dept. of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran
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