Web service creditworthiness measuring method based on context data of user

Abstract

A Web service creditworthiness measuring method based on context data of a user comprises the following steps: acquiring the context data of the user when the user accesses Web services, and pre-processing the context data, represented by vectors, of the user by using a normalization manner; clustering the pre-processed context data of the user by using a k-means method so as to conveniently represent the context data of the different users by using different types respectively; then, calculating the influences on feedback grades by using the user context data with the different types according to the user feedback grades and the clustered user context data; converting the feedback grades of the user context data with the different types into a unified reference grade so as to weaken the influences on the feedback grades by the user context data with the different types; and finally, calculating the user similarity according to the converted feedback grades to obtain service creditworthiness corresponding to the context data type of the reference user, and converting the service creditworthiness into the service creditworthiness corresponding to the context data types of the other users.

Description

technical field [0001] The invention relates to a user context-based Web service credibility measurement method, which belongs to the technical field of computer applications. Background technique [0002] Service-Oriented Architecture SOA (Service-Oriented Architecture) is a component model that connects different functional units (also called services) of applications through well-defined interfaces and contracts between these services. SOA technology has existed for more than 20 years, however, it has not been widely used. With the emergence of Web services, it has been gradually accepted by people, and SOA has finally ushered in its own "spring". [0003] In an open SOA environment, due to the influence of many factors, users cannot guarantee that the service QoS information issued by the service provider is objective, reliable and true at the same time. Therefore, it is very important for service selection to effectively measure the authenticity and credibility of the...

AI Technical Summary

Problems solved by technology

[0009] To sum up, although the existing Web service reputation measurement methods can effectively improve the accuracy of service reputation measurement, most of them have the following shortcomings: (1) The above methods regard all users as the same weight, that is, they consider All valid feedback users have the same impact factor, which is clearly inaccurate

(2) The above method ignores the environment in which the user uses the service and the impact of the equipment used, that is, the influence factor of the user context is ignored, and the feedback data in different environments is not treated differently

These problems lead to a certain degree of inaccuracy in the method

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