## 2 State-Of-The-Art
A trust management framework that is event-driven and rule-based in service-oriented computing environments was proposed by [PERSON], [PERSON] and [PERSON] [52]. The paper proposed trust evaluation metrics and trust computation formulas. The incremental characteristics of the trust establishment process were embodied in the proposed model. Reputation ranks were determined by a fuzzy-logic based approach in which new service providers and old ones were differentiated [25]. Service users are important information sources for the reputation of service providers, and transaction-feedback is used as the quality indicator for trust building in e-commerce. Unfair or incorrect information from unreliable or malicious users have significant negative effects on the fairness and objectivity of reputation evaluation. Therefore, the collaborative filtering method is used in reputation systems by different researchers in order to detect and isolate unfair or inaccurate information provided by unreliable or malicious users [18, 20]. In recent years, probability-based approaches such as the Bayesian model and the Dirichlet model [6, 17, 22, 59] are derived into trust and reputation computation. Online trust and reputation issues for B2C e-commerce have been investigated by researchers of different disciplines, yet there are further issues that remain to be solved. (1) There are some practical reputation rating systems of B2C e-commerce such as taobao (www.taobao.com), dangdang (www.dangdang.com) and 360 buy (www.360 buy.com). In these reputation evaluation systems, ratings and reviews of users are stored. The reputation rankings of these systems are mainly based on simple means algorithms. Theoretical research on the reputation systems is also put forward [9, 18, 59, 60, 61]. However, the rating algorithms are particularly simple. We know that reputation is a long-term process during which trust is established. How to describe the characteristics of trust and reputation is one goal for this research. (2) The temporal relationship of trust and reputation are not considered in previous research projects [14, 15, 16, 18, 22, 52, 53]. In terms of both real life and theory, the reason that certain things or service providers are trusted may be their positive reputation. On the other hand, reputation is built via word-of-mouth and trust. So a reputation computation model for B2C e-commerce will be investigated by trust values from reviewers. Reputation is aggregated by several aspects, such as trust values, different reviewers, different time, and different transactions. The temporal relationship of trust and reputation is included in our proposed computation model. The closed-loop iterative computation model is established, which is based on the conceptions of local trust and overall reputation. (3) How to design a fair and optimal reputation management system is still an open problem for both practical usages of website services, such as B2C e-commerce and theoretical research of the reputation system. Centralized and distributed management architectures are two design options [52,55,60]. In centralized reputation management systems, reviews of service clients are independent of service providers [2,52]. We adopt centralized management architecture in the proposed reputation computation model. The dynamical trust computation model is put forward, in which different aspects of various factors are considered. A reputation evaluation system is further established by fusing trust values. An iterative trust and reputation computation model is further proposed. The proposed evaluation method is intended to be relatively fair and objective. B2C e-commerce is defined as consumers purchasing products and services via the Internet, otherwise known as online shopping. Trust in B2C e-commerce is associated with consumer experiences, asymmetry of information, interval of space and time of transactions, and transaction risk [62,63]. The conception of trust in B2C e-commerce can be outlined as follows.