Web service quality prediction method based on random walk

Abstract

The invention discloses a Web service quality prediction method based on random walk. The Web service quality prediction method comprises the following steps: on the basis of a user position, calculating a distance between users; selecting adjacent users for each user to form a neighborhood, and connecting neighborhood users to construct a user relationship network; calculating a similarity between the users and the similarity between services in the user relationship network; calculating the weight of each edge in the user relationship network; aiming at a target service requested by a source user to independently look up the random walk about the target service i for multiple times from the source user, randomly selecting a next-hop node by each hop in each-time random walk according to a certain probability, returning a QoS value after each-time walk is finished; and synthesizing all QoS values to calculate a quality prediction value, which is relative to the target service, of the source user. The Web service quality prediction method can balance coverage rate and the prediction precision of Web service quality prediction and has the advantages of being accurate in prediction, high in success rate, good in universality and favorable in evaluable confidence coefficient and interpretability.

Description

technical field [0001] The invention relates to Web service quality prediction technology, in particular to a random walk-based Web service quality prediction method for Web service selection or recommendation. Background technique [0002] Web service is a self-describing and self-contained available network module, which is used to help realize the interactive operation between different machines through remote calls, and has become the main technology for constructing distributed systems, modular applications and service-oriented application integration. , such as e-commerce, vehicle systems, multimedia services, etc. With the rapid growth of the number of Web services on the network, it becomes more challenging to recommend the optimal service for users. In order to find the optimal service among a large number of alternative Web services with the same function, the quality of Web services, that is, QoS (Quality of Service), is widely used to describe and evaluate the n...

AI Technical Summary

Problems solved by technology

[0004] In the prior art, the most commonly used method for predicting missing QoS values ​​has the following defects: 1) Due to the rapid increase in the number of Web services and users, there is a problem of data sparsity, which makes it difficult for collaborative filtering methods to solve the "cold start" problem, that is, a certain The user has never called any service, or a service has never been called by any user

However, only considering user location to predict QoS may reduce the prediction accuracy

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