The HMM-based model for evaluating recommender's reputation

Weihua Song, Vir V. Phoha, Xin Xu

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

5 Scopus citations

Abstract

There is limited research on evaluating an agent's reputation as a recommender. A key challenge is that a recommender's reputation is affected by both the recommender's trustworthiness and the recommender's expertise, including the recommender's trust knowledge of others and the reliability of the recommender's trust evaluation models. In this paper, we give an ordered depth-first search with threshold (ODFST) algorithm to find the optimal referral chain. We then develop a Hidden Markov Model (HMM) based approach to measure an agent's reputation as a recommender. This approach models chained recommendation events as an HMM. The features of the trust model are: (1) no explicit requirement of chained recommendation reputations; (2) flexible recommendation network with presence of loops; and (3) integration of learning speed into trust evaluation reliability. The experimental results showed the convergence and reliability of the proposed trust model.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE International Conference on E-Commerce Technology for Dynamic E-Business, CEC-East 2004
EditorsK.-J. Lin, T. Li
Pages209-215
Number of pages7
StatePublished - Dec 1 2004
EventProceedings of the IEEE International Conference on E-Commerce Technology for Dynamic E-Business, CEC-East 2004 - Beijing, China
Duration: Sep 13 2004Sep 15 2004

Publication series

NameProceedings of the IEEE International Conference on E-Commerce Technology for Dynamic E-Business, CEC-East 2004

Other

OtherProceedings of the IEEE International Conference on E-Commerce Technology for Dynamic E-Business, CEC-East 2004
CountryChina
CityBeijing
Period9/13/049/15/04

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Song, W., Phoha, V. V., & Xu, X. (2004). The HMM-based model for evaluating recommender's reputation. In K-J. Lin, & T. Li (Eds.), Proceedings of the IEEE International Conference on E-Commerce Technology for Dynamic E-Business, CEC-East 2004 (pp. 209-215). (Proceedings of the IEEE International Conference on E-Commerce Technology for Dynamic E-Business, CEC-East 2004).