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    题名: A Learning-Enabled Integrative Trust Model for E-Markets
    作者: 苑守慈;Hao Sung
    贡献者: 資管系
    日期: 2004-01
    上传时间: 2009-01-17 16:33:43 (UTC+8)
    摘要: Existing e-markets presume no deception from agents or else they employ simple mechanisms to counteract deception. However, the reality shows that agents in e-markets can either cheat or break contracts due to higher benefits elsewhere, which is similar to what we find in humanity in general. Accordingly, the notion of trust in human society should be implemented in e-markets. Most of the existing research on trust is modeled theoretically from different views, and hence it is not easy to deploy them in e-markets due to the naturally non-computable essence of trust. However, current computable trust mechanisms, such as those used in eBay and Nextag, uniformly manipulate trust involved in all trading, resulting in complaints about non-differentiated experience. On the other hand, a computable trust model can help the formation of coalitions in e-markets and increase market competition. In this paper, we present a simple heuristic trust model absorbing the predominant views of trust with which agents in e-markets can better evaluate possible trading partners before trading processes take place. In this model, trust is characterized by the properties of being computable, individualized, evolutional, represented by scores, and extendable to the computation of coalition trust.
    關聯: Applied Artificial Intelligence, 18(1), 69-95
    数据类型: article
    DOI 連結: http://dx.doi.org/10.1080/08839510490250105
    DOI: 10.1080/08839510490250105
    显示于类别:[資訊管理學系] 期刊論文

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