A Fuzzy Trust Model for E-Commerce

Abstract

Abstract:Although, there are many successful E-commerce organizations, it is argued that E-commerce has not reached its full potential. Trust was often cited as the main reason as many customers are still skeptical about some online vendors. Many trust models have been developed, but most are subjective and did not take into account the vagueness and ambiguity of the domain and the specificity of customers. We have developed a model that attempts to identify the information customers expect to find on a vendors website to increase their trust and hence the likelihood of a transaction to take place. The system is supported by an information extraction system that facilitates the information gathering process. In this paper, we present a method based on fuzzy logic to evaluate trust in E-commerce based on the extracted information. We argue that fuzzy logic is suitable for trust evaluation as it takes into account the uncertainties within E-commerce data and like human relationships, trust is often expressed by linguistics terms rather then numerical values. The results of the system validation using two case studies are also presented.

A trust model for new member in multiagent system

“…For instances, Grandison and Sloman [6] define trust as a quantified belief by a truster with respect to the competence, honesty, security and dependability of a trustee within a specified context. The model given by Nefti et al [16] considers some kind of information on a merchant website that is shown to increase customer trust. Abdul-Rahman and Hailes [1] make use of four degrees of belief to typify agent trustworthiness: vt (very trustworthy), t (trustworthy), u (untrustworthy) and vu (very untrustworthy).…”

“…Many models of computational trust for multiagent systems have been proposed such as Grandison and Sloman [6], Nefti et al [16], Yu and Singh [30][31][32], Sen and Sajja's [26], Carter et al [4], Ramchurn et al [22], Huynh et al [12,13], Victor et al [28], Nguyen and Tran [17][18][19], Katz and Golbeck [14], Hang et al [8], Guha et al [7], Vogiatzis et al [29]. Most of such models are based on two sources of information.…”

A fuzzy agent-based approach to trust-based competency management

“…At the same time, it is " a mental state comprising expectancy (the trustor expects a specific behavior from the trustee) and belief" [3]. Computational trust models have recently been drawing the attention of many scientific communities from various disciplines [6], [7] to analyze interpersonal or inter-organizational trust in different domains such as e-commerce [8] and social web applications [9].…”

A Trust-based Mechanism for Avoiding Liars in Referring of Reputation in Multiagent System

“…29 | P a g e www.ijarai.thesai.org [4] Guha et al [9] Hang et al [10] Hermoso et al [11] Jennings et al [12], [13] Katz and Golbeck [16] Lashkari et al [17] Li and Gui [18] Manchala [19] Nefti et al [20] Nguyen and Tran [22], [23] Ramchurn et al [24] Sabater and Sierra [26], [27] Schillo et al [28] Sen and Sajja's [29] Shibata et al [30] Singh and colleagues [36], [37] Teacy et al [31], [32] Victor et al [33] Vogiatzis et al [34] Whitby et al [35] Zhang, Robin and collegues [39], [14], [5], [6] Our model…”

“…Firstly, The models are based on personal experiences that a truster has on some trustee after their transactions performed in the past. For instance, Manchala [19] and Nefti et al [20] proposed models for the trust measure in e-commerce based on fuzzy computation with parameters such as cost of a transaction, transaction history, customer loyalty, indemnity and spending patterns. The probability theory-based model of Schillo et al [28] is intended for scenarios where the result of an interaction between two agents is a boolean impression such as good or bad but without degrees of satisfaction.…”