Social recommendation method based on trust relationship implicit similarity

A technology of trust relationship and recommendation method, applied in instruments, network data retrieval, marketing, etc., can solve the problems of unreliable trust degree and lack of effective information, and achieve the effect of improving robustness and estimation accuracy.

Inactive Publication Date: 2017-01-25
WUHAN UNIV
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Problems solved by technology

However, these similarities are all calculated based on common ratings or friend sets. For the calculation of trust between users, when the ratings or trust data are very sparse, there is less effective information, and the trust obtained by the direct calculation method is not Unreliable

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  • Social recommendation method based on trust relationship implicit similarity
  • Social recommendation method based on trust relationship implicit similarity
  • Social recommendation method based on trust relationship implicit similarity

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[0014] In order to facilitate the understanding and implementation of the present invention by those of ordinary skill in the art, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0015] Please see figure 1 , The present invention provides a social recommendation method based on implicit similarity of trust relationship, including the following steps:

[0016] 1. Use the method of probability matrix decomposition to calculate the user's trust and trusted vector:

[0017] a) Let with Respectively represent the preference vector when user u is the trustee and the trustee, and the characteristic dimension is K. A Gaussian distribution with a mean value of 0 and a variance of 0.1 is used for initialization.

[0018] b) Loss functio...

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Abstract

The invention discloses a social recommendation method based on trust relationship implicit similarity. Firstly, trust and trusted vectors of users are obtained through the probability matrix decomposition, wherein the vectors imply direct and indirect association between the users, and accordingly sparse scoring and information in trust data are mined more sufficiently; secondly, trust relationship implicit similarity of the users can be obtained through the probability estimation method, and accordingly estimation precision of trust relationship strength is improved; finally, scoring similarity between the users is comprehensively taken into consideration, and robustness of the algorithm under the data sparsity condition is further improved.

Description

Technical field [0001] The invention belongs to the field of data mining and big data, and particularly relates to a social recommendation method based on implicit similarity of trust relationships. Background technique [0002] In daily life, with the continuous development of network information, the problem of information overload becomes more and more serious. How to obtain effective information from massive amounts of data is a huge challenge for ordinary users. Recommendation algorithm is one of the important means to solve this problem. By modeling the user's historical behavior, it actively provides users with products that meet the users' potential preferences. For users, the recommendation system can help them quickly find satisfactory information in a large amount of information; for businesses, the recommendation system can not only help decide which products to promote to specific users, but also increase user loyalty through more satisfactory services. degree. Re...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06Q50/00G06Q30/02
CPCG06F16/958G06Q30/0201G06Q50/01
Inventor 何发智潘一腾
Owner WUHAN UNIV
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