Inferring trust using relation extraction in heterogeneous social networks

Nima Haghpanah, Masoud Akhoondi, Hassan Abolhassani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publicationAdvances in Computer Science and Engineering - 13th International CSI Computer Conference, CSICC 2008, Revised Selected Papers
Pages867-870
Number of pages4
DOIs
StatePublished - Dec 1 2008
Event13th International Computer Society of Iran Computer Conference on Advances in Computer Science and Engineering, CSICC 2008 - Kish Island, Iran, Islamic Republic of
Duration: Mar 9 2008Mar 11 2008

Publication series

NameCommunications in Computer and Information Science
Volume6 CCIS
ISSN (Print)1865-0929

Other

Other13th International Computer Society of Iran Computer Conference on Advances in Computer Science and Engineering, CSICC 2008
CountryIran, Islamic Republic of
CityKish Island
Period3/9/083/11/08

Fingerprint

Electric network analysis
Fuzzy logic
Genetic algorithms
Uncertainty

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)

Cite this

Haghpanah, N., Akhoondi, M., & Abolhassani, H. (2008). Inferring trust using relation extraction in heterogeneous social networks. In Advances in Computer Science and Engineering - 13th International CSI Computer Conference, CSICC 2008, Revised Selected Papers (pp. 867-870). (Communications in Computer and Information Science; Vol. 6 CCIS). https://doi.org/10.1007/978-3-540-89985-3_121
Haghpanah, Nima ; Akhoondi, Masoud ; Abolhassani, Hassan. / Inferring trust using relation extraction in heterogeneous social networks. Advances in Computer Science and Engineering - 13th International CSI Computer Conference, CSICC 2008, Revised Selected Papers. 2008. pp. 867-870 (Communications in Computer and Information Science).
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Haghpanah, N, Akhoondi, M & Abolhassani, H 2008, Inferring trust using relation extraction in heterogeneous social networks. in Advances in Computer Science and Engineering - 13th International CSI Computer Conference, CSICC 2008, Revised Selected Papers. Communications in Computer and Information Science, vol. 6 CCIS, pp. 867-870, 13th International Computer Society of Iran Computer Conference on Advances in Computer Science and Engineering, CSICC 2008, Kish Island, Iran, Islamic Republic of, 3/9/08. https://doi.org/10.1007/978-3-540-89985-3_121

Inferring trust using relation extraction in heterogeneous social networks. / Haghpanah, Nima; Akhoondi, Masoud; Abolhassani, Hassan.

Advances in Computer Science and Engineering - 13th International CSI Computer Conference, CSICC 2008, Revised Selected Papers. 2008. p. 867-870 (Communications in Computer and Information Science; Vol. 6 CCIS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Haghpanah N, Akhoondi M, Abolhassani H. Inferring trust using relation extraction in heterogeneous social networks. In Advances in Computer Science and Engineering - 13th International CSI Computer Conference, CSICC 2008, Revised Selected Papers. 2008. p. 867-870. (Communications in Computer and Information Science). https://doi.org/10.1007/978-3-540-89985-3_121