Personalized recommendation method and system based on user attribute knowledge base
A technology of user attributes and recommendation system, applied in the field of recommendation, can solve the problems of wrong recommendation, reduce the value of recommendation system to users, and reduce the adoption rate of recommendation results by users, so as to improve the accuracy, meet the needs of personalized recommendation, and enhance the value Effect
Active Publication Date: 2020-11-13
SOUTH CHINA NORMAL UNIVERSITY
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Problems solved by technology
It can be seen that the recommendation results obtained by existing recommendation technologies often do not match the products that users want to buy, resulting in wrong recommendations, which in turn reduces the user's adoption rate of the recommendation results and reduces the value of the recommendation system to users.
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[0026] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, and do not limit the protection scope of the present invention.
[0027] A personalized recommendation method in one embodiment, such as figure 1 shown, including the following steps:
[0028] Step S101: Obtain the recommendation result sequence recommended by the current recommendation system to the user;
[0029] Among them, the current recommendation system can be various existing recommendation systems, or a newly developed recommendation system; the recommendation results recommended by the recommendation system to users can be various types of recommendation results, for example, product recommendations, clothing recommendations...
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The present invention discloses a personalized recommendation method and system. The method comprises the steps of obtaining a recommendation result sequence recommended by a current recommendation system to a user; obtaining a preset first recommendation number of recommendation results in a preset first direction in the recommendation result sequence as an initial recommendation result sequence; querying whether to store the attribute of the user according to the identity information of the user; when a query result is yes, matching the recommendation results in the initial recommendation result sequence with the attribute of the user separately; according to a matching result and a preset principle, ranking the recommendation results in the initial recommendation result sequence; obtaining a preset second recommendation number of recommendation results in a preset second direction in the ranked recommendation result sequence as a final recommendation result sequence; outputting the final recommendation result sequence. According to the present invention, the accuracy of recommending the user is improved, and further the adoption rate of the user to the recommendation result and the value of the recommendation system to the user are improved.
Description
technical field [0001] The invention relates to the technical field of recommendation, in particular to a personalized recommendation method and system based on a user attribute knowledge base. Background technique [0002] With the continuous expansion of the scale of e-commerce, the number and types of commodities increase rapidly, and users need to spend a lot of time to find the commodities they want to buy. The process of browsing a lot of irrelevant information and products will undoubtedly lead to continuous loss of consumers. In order to solve these problems, personalized recommendation technology came into being. Personalized recommendation technology is an advanced business intelligence platform based on massive data mining to help e-commerce sites provide fully personalized decision support and information services for their customers. [0003] However, when the existing personalized recommendation system recommends based on the analysis of the historical data o...
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IPC IPC(8): G06F16/00G06F16/55
CPCG06Q30/0271G06Q30/0277
Inventor 朱定局
Owner SOUTH CHINA NORMAL UNIVERSITY