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Personalized recommending method fused with user trust relationships and comment information

A technology of trust relationship and recommendation method, which is applied in special data processing applications, instruments, electrical digital data processing, etc., and can solve problems such as inaccurate recommendation results

Inactive Publication Date: 2017-05-17
GUANGDONG UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

[0014] Aiming at the problem of inaccurate recommendation results generated by the recommendation system due to sparse user scoring data and cold start problems, the purpose of the present invention is to provide a collaborative filtering recommendation method that integrates edge data such as user trust relationship and user usefulness evaluation

Method used

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  • Personalized recommending method fused with user trust relationships and comment information
  • Personalized recommending method fused with user trust relationships and comment information
  • Personalized recommending method fused with user trust relationships and comment information

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Embodiment Construction

[0044] The present invention will be further described in detail through examples and drawings.

[0045] The prerequisite for the implementation of the invention is that user project rating data, user trust relationship data, and user usefulness evaluation data have been obtained.

[0046] figure 1 It is a schematic flow diagram of a collaborative filtering recommendation method integrating preference trust relationships provided by an embodiment of the present invention, such as figure 1 As shown, this embodiment mainly includes the following steps:

[0047] Step S1: Calculate the similarity between users Sim according to the following formula according to the user item rating matrix, construct a user similarity relationship matrix, and calculate Simij as the value of the element in the matrix.

[0048]

[0049] figure 2 A schematic diagram of a matrix of user item rating data. U1,..., U5 represent users, I1,..., I6 represent items. User ratings have 5 levels, namely 1, 2, 3, 4, an...

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Abstract

The invention discloses a personalized recommending method fused with user trust relationships and comment information. The method includes adding useful comments and user trust relationships on the basis of performing probability decomposition on a score matrix, wherein the user trust relationships explicitly show the trust level of users, the user useful comment information potentially shows the trust level of the users, and the two aspects of information can predict interests and hobbies of the users; and an alternating least squares is used to train model parameters. The personalized recommending method can fuse user trust relationships in a credible network and the potential trust relationships acquired by the useful comment behaviors, and can improve the recommendation precision.

Description

Technical field [0001] The present invention relates to the field of computer data processing technology, in particular to the multi-source data technology of user trust network and usefulness evaluation behavior in personalized recommendation. Background technique [0002] As an effective means to relieve the information load, the personalized recommendation system obtains user characteristics or predicts user behavior by analyzing the user's historical behavior data. However, with the rapid increase in the number of users, it is very difficult to construct user interest models and predict user behaviors under the condition of limited behavioral data. The matrix factorization method aims to use two or more low-dimensional matrices to approximate a high-dimensional matrix. This method can remove noisy users or noisy items, and reduce the dimension of the user's item score matrix to obtain potential relationships between users or items , So as to obtain better prediction accuracy...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 增安徐小强黎建忠
Owner GUANGDONG UNIV OF TECH
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