Collaborative filtering recommendation method based on optimal trust path

Abstract

The invention discloses a collaborative filtering recommendation method based on an optimal trust path, which is improved by aiming at a traditional collaborative filtering algorithm and a trust fusion collaborative filtering algorithm, and comprises the following steps of: firstly, constructing a trust network of users, calculating trust degrees among the users, and calculating interest similarity among the users; calculating the comprehensive similarity among the users by combining the trust degree among the users and the interest similarity among the users; obtaining a nearest neighbor setaccording to the comprehensive similarity among the users; and finally predicting the score of the target user to the project to obtain a project recommendation result. According to the method, a global user is considered during calculation; a multi-path trust degree algorithm is provided on the basis of the fused trust recommendation algorithm; the optimal path is selected from multiple trust paths to represent the path trust degree between two users, the trust weight relationship contained in the path is considered, the recommendation accuracy and the operation efficiency of the algorithm are improved, and the operation time of the algorithm is about 1 / 4 of the operation time of the existing fusion trust recommendation algorithm.

Description

technical field [0001] The invention relates to the technical field of personalized recommendation, in particular to a broadband noise signal generator and a generating method thereof. Background technique [0002] With the continuous development of the Internet and information technology, people can freely publish and download information and various electronic resources on the Internet, forming a rich information space around the world. However, in a large number of information networks, users cannot quickly find valuable information within a limited time, resulting in reduced information utilization and the formation of information overload problems. The recommendation system can greatly improve the utilization rate of information and provide people with personalized recommendation services. Its quality depends on the recommendation algorithm, which can be divided into three categories at present. The first category is collaborative filtering recommendation algorithm, th...

AI Technical Summary

Problems solved by technology

[0008] The present invention provides a collaborative filtering recommendation method based on the best trust path in order to solve the problems of low recommendation accuracy and slow operating efficiency in the existing collaborative filtering recommendation algorithm

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