Discovering relationship types between users using profiles and shared photos in a social network

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• 作者：Elie Raad (1)
  Richard Chbeir (1)
  Albert Dipanda (1)
  
• 关键词：Social networks ; Link type prediction ; Photo based inference ; User profile ; Photo metadata ; Rule mining
• 刊名：Multimedia Tools and Applications
• 出版年：2013
• 出版时间：May 2013
• 年：2013
• 卷：64
• 期：1
• 页码：141-170
• 全文大小：3,324 KB
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• 作者单位：Elie Raad (1)
  Richard Chbeir (1)
  Albert Dipanda (1)
  
  1. LE2I-CNRS, Bourgogne University, Dijon, France
  
• ISSN：1573-7721

文摘

In this paper, we propose a new approach to discover the relationship types between a user and her contacts in a social network. This is of key importance for many applications in the domain of photo sharing, privacy protection, information enriching, etc. Our approach is based, on one hand, on information extracted from users-profiles and their shared photos, and, on the other hand, on a set of predefined rules validated by the main user before being mined and derived according to her preferences and social network content. The contribution of our method is twofold: 1) it is user-based enabling the user to set her preferences and give her feedbacks on the derived rules and results, and 2) it is multi-criteria that exploits and combines several attributes and features from user profiles and shared photos respectively. It also allows the user to define new relationship types. We conducted a set of experiments to validate our approach. The obtained results show the accuracy of our approach in different scenarios.