Commodity recommendation method and device for deep learning, computer device and storage medium
A product recommendation and deep learning technology, applied in the field of artificial intelligence, can solve the problem of low accuracy of product information, achieve the effects of increasing convergence speed, improving prediction accuracy, and enhancing influence
Active Publication Date: 2020-02-21
CHINA PING AN LIFE INSURANCE CO LTD
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[0003] The purpose of the embodiment of this application is to propose a product recommendation method based on deep learning to solve the problem of low accuracy of recommended product information in traditional product recommendation methods
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[0062]Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field of the application; the terms used herein in the description of the application are only to describe specific embodiments The purpose is not to limit the present application; the terms "comprising" and "having" and any variations thereof in the specification and claims of the present application and the description of the above drawings are intended to cover non-exclusive inclusion. The terms "first", "second" and the like in the description and claims of the present application or the above drawings are used to distinguish different objects, rather than to describe a specific order.
[0063] Reference herein to an "embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. The occurrence...
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The invention discloses a commodity recommendation method and device for deep learning, a computer device and a storage medium, and relates to the field of artificial intelligence. The method comprises the steps of obtaining a commodity list of a user, wherein the commodity list comprises commodity information; vectorizing the commodity information; obtaining a mean vector corresponding to the commodity information; inputting the mean vector into a preset recommendation model for commodity classification, to output commodity recommendation information corresponding to mean vector and recommendcommodity recommendation information to user. According to the method, the accuracy of commodity recommendation prediction is improved, the recommendation information is more personalized, and the problem that a traditional recommendation model has thousands of people, namely single recommended commodity information, is avoided.
Description
technical field [0001] This application relates to the field of artificial intelligence, and in particular to a product recommendation method, device, computer equipment and storage medium of deep learning. Background technique [0002] With the rapid development of e-commerce websites, e-commerce websites have accumulated a large amount of user data, including user basic information, user purchase behavior data, user browsing and collection data, and item information. How to analyze and mine the accumulated massive user data, build a user purchase model and recommend items to users is a hot issue in the optimization model of e-commerce websites. However, the recommended products output by the traditional model tend to be popular products. This kind of recommendation method has the problem of repeated information recommendation, that is, the recommendation content is the same for thousands of people, which makes the prediction accuracy of information recommendation not high....
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IPC IPC(8): G06Q30/06G06N3/04G06N3/08G06K9/62
CPCG06Q30/0631G06N3/08G06N3/045G06F18/241
Inventor 陈楚
Owner CHINA PING AN LIFE INSURANCE CO LTD