Research And Implementation Of Online Service Reputation Measurement Method Based On Kendall Tau Distance

With the development and popularization of the Internet,the traditional business environment is transformed into an open,shared,and diverse online service-oriented approach.Online services play an increasingly important role in e-commerce,business management,and management.There are more and more online services available to users on the Internet.At the same time,users also need to spend more time and effort to find themselves.Required services: On the one hand,the large number of online services makes it impossible for users to have interactive experience with each online service,and users cannot obtain complete information for each online service.On the other hand,some users or online service providers may provide unrealistic evaluation information to the service because the network environment allows anonymous interaction without direct contact with each other.Therefore,the user usually needs to use the reputation of the online service formed on the basis of the third party view to assist in service selection.In an open and dynamic online network environment,different users have different consumer preferences and consumption histories.Their preferences for online services are different,resulting in different users’ ratings of the same service are not comparable.It is difficult to obtain an objective service reputation without considering the user’s preferred reputation mechanism.The obtained service reputation is necessarily unobjective,and even results that mislead consumers to choose.Therefore,this paper fully considers the preference of different users for services,and proposes an online service reputation measurement method based on Kendall tau distance.The method first defines the distance index to measure the consistency between the two score vectors,and then builds the online service reputation measurement.The module seeks an optimization problem with a minimum reputation vector from the user-service scoring matrix.Finally,the simulated annealing algorithm is used to solve the optimization problem,and the obtained reputation vector is used as the service reputation.The paper does not assume that the user’s preferences are the same.Based on the user’s rating,the Kendall tau distance measurement method is used to obtain the same user’s preference relationship for different online services.Aggregating these preference relationships ultimately results in service reputation.Since the same rational user’s rating is comparable,this solves the problem that the above different user ratings are not comparable.By considering the user’s rating of different services,the anti-handling of the reputation mechanism is improved,the risk of reputation manipulation is reduced,and the reputation vector with the smallest distance from the user-service scoring matrix is used as the service reputation to satisfy most users’ preferences.And to a certain extent,the efficiency of reputation metrics is improved.Theoretical analysis and experiments verify the rationality and effectiveness of the method.Finally,according to the reputation measurement method proposed in this paper,an online service reputation measurement system based on Kendall tau distance is designed and implemented.