e-journal
A Novel Method for Calculating Service Reputation
Owing to their rapid development, services are increasing rapidly in quantity. The consequence is that there are so many services that share the same or similar functions. Therefore, it is important to select a credible and optimal service. Reputation as one of the important parameters of services plays a significant role in the decision support for service selection. This paper proposes a novel two-phase method to calculate service reputation. The first phase uses a dynamic weight formula to calculate
reputation such that it can reflect the latest tendency of a service. The second one uses an olfactory response formula to mitigate the negative effect of unfair ratings. Some experiments are conducted
and the results validate the effectiveness of the proposed method. Note to Practitioners—Reputation is an important factor for users to select the most desired one among many services. Therefore, it is of great significance to calculate its reputation accurately according to historical ratings that prior users gave to a service. However, the methods used by many commercial corporations, such as Amazon and eBay, have some serious deficiencies, i.e., they can neither reflect the latest tendency of reputation changes
nor filter unfair ratings that distort a service’s true reputation. In order to improve the existing methods, this paper proposes a method to calculate the reputation of a service, which is motivated
by an olfactory fatigue phenomenon. The experimental results show that the proposed method is more accurate than others. It can thus help users select more appropriate services and then raise
their positive experiences, which in turn promotes the competitive advantages of the companies using it.
Index Terms—Business, electronic commerce, olfactory response, particle swarm optimization, performance evaluation, service reputation, web service, workflow.
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