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Inferring trust using relation extraction in heterogeneous social networks

Haghpanah, N ; Sharif University of Technology | 2008

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  1. Type of Document: Article
  2. DOI: 10.1007/978-3-540-89985-3_121
  3. Publisher: 2008
  4. Abstract:
  5. People use trust to cope with uncertainty which is a result of the free will of others. Previous approaches for inferring trust have focused on homogeneous relationships and attempted to infer missing information based on existing information in a single relationship. In this paper we propose using methods of social network analysis to infer trust in a heterogeneous social network. We have extended the problem of relation extraction and allowed using any type of binary operator on matrixes, whereas previous work have focused on linear combination of base matrixes (the only allowed operator was summation of two matrixes). We present two genetic algorithms which use ordinary numerical and fuzzy logic operators and compare them on a real world dataset. We have verified our claim - ability to infer trust in a heterogeneous social network- using proposed methods on a web-based social network. © 2008 Springer-Verlag
  6. Keywords:
  7. Base matrix ; Binary operators ; Data sets ; Free will ; Fuzzy logic operators ; Graph mining ; Linear combinations ; Matrix ; Missing information ; Relation extraction ; Social network analysis ; Social networks ; Trust ; Trust Model ; Computer science ; Electric network analysis ; Fuzzy logic ; Mathematical operators
  8. Source: 13th International Computer Society of Iran Computer Conference on Advances in Computer Science and Engineering, CSICC 2008, Kish Island, 9 March 2008 through 11 March 2008 ; Volume 6 CCIS , 2008 , Pages 867-870 ; 18650929 (ISSN); 3540899847 (ISBN); 9783540899846 (ISBN)
  9. URL: https://link.springer.com/chapter/10.1007/978-3-540-89985-3_121