Collaborative filtering recommendation method based on optimal trust path
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A collaborative filtering recommendation and path technology, applied in digital data information retrieval, instrumentation, electronic digital data processing, etc., can solve the problems of slow operation efficiency and low recommendation accuracy
Active Publication Date: 2020-04-10
GUANGDONG POLYTECHNIC NORMAL UNIV
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[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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Embodiment 1
[0085] A collaborative filtering recommendation method based on the best trust path, such as figure 1 with figure 2 shown, including the following steps:
[0086] S1. Construct the user's trust network and calculate the trust degree between users. The trust degree between users includes: according to the type of trust path to which the current user's trust data belongs, the corresponding path trust degree between users is calculated, and then combined with the common interest factor among users, Get the trust degree between users; Image 6 As shown, the trust path type includes direct path trust and indirect path trust, wherein indirect path trust includes single path trust and multipath trust;
[0087] The following is a detailed description of Step S1 of Embodiment 1:
[0088] 1. Build a trust network for users:
[0089] Such as Figure 4 As shown, the trust relationship of users in the social network is represented by a directed graph G=, where V represents the set of...
Embodiment 2
[0157] This implementation 2 is based on the experiment and analysis of embodiment 1, and the content of the experiment and analysis is divided into the following four parts:
[0158] (1) Explore the setting of parameters in the original algorithm, and analyze the impact of each parameter on the performance of the recommendation system;
[0159] (2) compare the inventive method (OPTCF), the collaborative filtering recommendation algorithm (FTCF) of fusion trust and the traditional user-based collaborative filtering recommendation algorithm (UCF) through experiments;
[0160] (3) verify the stability of the inventive method (OPTCF), the collaborative filtering recommendation algorithm (FTCF) of fusion trust and the traditional user-based collaborative filtering recommendation algorithm (UCF) in different environments;
[0161] (4) Explore the running time of the algorithm and analyze the reasons that affect the running time.
[0162] The detailed description of this experiment...
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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...
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