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Cross-domain recommendation data processing method with multiple auxiliary domains and cross-domain recommendation system

A technology for recommending data and processing methods, which is applied in the directions of instruments, sales/lease transactions, character and pattern recognition, etc., and can solve the problems of non-mixable use and cross-domain recommendation of multiple auxiliary domains.

Inactive Publication Date: 2019-05-03
XIDIAN UNIV
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Problems solved by technology

[0005] To sum up, the problems existing in the existing technology are: the existing technology is aimed at the cold-start user problem in the target domain when there are anchor users in the two domains, and cannot make cross-domain recommendations for the case of multiple auxiliary domains
Second, users have different preferences and behavioral characteristics in different fields, and the scoring data in different fields cannot be simply mixed
Third, although the preferences and characteristics of the same user in different domains are related, they also vary greatly

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  • Cross-domain recommendation data processing method with multiple auxiliary domains and cross-domain recommendation system

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Embodiment Construction

[0067] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0068] The existing technology is aimed at the problem of cold-start users in the target domain when there are anchor users in the two domains, and cannot perform cross-domain recommendation in the case of multiple auxiliary domains. The present invention has a cross-domain recommendation method with multiple auxiliary domains, which alleviates the problem of unsatisfactory recommendation effect caused by the poor prediction accuracy of the traditional single auxiliary domain matrix decomposition model, improves the recommendation effect of the recommendation system, and has more versatility.

[0069] The application princi...

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Abstract

The invention belongs to the technical field of e-commerce information processing, and discloses a cross-domain recommendation data processing method with multiple auxiliary domains and a cross-domainrecommendation data processing system. The method comprises obtaining a scoring matrix of an auxiliary domain, calculating the scoring reliability of a user, carrying out equal-proportion segmented mapping on a threshold value, and emptying scores with the number of scores lower than the threshold value in the auxiliary domain; obtaining clustering level scoring matrix of all domains by using a K-means clustering algorithm, and carrying out matrix decomposition; meanwhile, decomposing the target domain scoring matrix to learn a feature mapping function for the cold start user; evaluating predicted scoring matrix by using an average absolute error. Compared with the prior art, the method has the advantages that K-means clustering algorithm is used in the data processing process for obtaining clustering-level user project scoring matrix combined with all domains, the data sparsity of the cold start user is reduced. The problem that the recommendation effect is not ideal due to poor prediction accuracy of a traditional single auxiliary domain matrix factorization model is solved, the recommendation effect of the recommendation system is improved, and the method has higher universality.

Description

technical field [0001] The invention belongs to the technical field of e-commerce information processing, and in particular relates to a cross-domain recommendation data processing method with multiple auxiliary domains and a cross-domain recommendation data processing system. Background technique [0002] At present, the existing technologies commonly used in the industry are as follows: With the rapid development of Internet technology and Web technology, e-commerce has become a new form of business activities, and more and more consumers are willing to purchase the commodities they need through the Internet. Through online shopping, consumers can browse a variety of products; compared with traditional offline shopping, online shopping enables consumers to have more choices. But on the other hand, the fast update speed of all kinds of information on the Internet makes it easy for consumers to get lost in a wide variety of "product oceans". While bringing many conveniences...

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Application Information

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IPC IPC(8): G06Q30/06G06K9/62
Inventor 乔慧沈玉龙董学文姜晓鸿佟威刘洋洋马诗洋谷鑫雨杨凌霄赵六顺
Owner XIDIAN UNIV
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