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Online commodity recommendation method based on user novelty

A product recommendation and user technology, applied in business, data processing applications, instruments, etc., can solve problems such as no clear shopping goals

Pending Publication Date: 2020-09-29
SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The specific manifestation is that after online shoppers enter the shopping channel, they no longer search for keywords and have no clear shopping goals, but they still stay for a long time.

Method used

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  • Online commodity recommendation method based on user novelty
  • Online commodity recommendation method based on user novelty
  • Online commodity recommendation method based on user novelty

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Experimental program
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Embodiment Construction

[0057] Embodiments of the present invention will be described in detail below. It should be emphasized that the following description is only exemplary and not intended to limit the scope of the invention and its application.

[0058] On the one hand, the recommended products can meet the curiosity-seeking needs of consumers in more and more passive recommendation scenarios. Users do not need to enter search information, the system can recommend products based on the user's historical click behavior, and the recommended content can match the user's curiosity-seeking mentality. On the other hand, it promotes users to click and browse recommended dwell time. Driven by curiosity, users will choose to view fresh content they are interested in, and may also repeatedly browse product information similar to purchased products. A reasonable allocation of the ratio of old and new recommendations can lead to higher user satisfaction.

[0059] In order to make personalized recommendat...

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Abstract

The invention discloses an online commodity recommendation method based on user novelty. The method comprises the following steps: S1, forming a selection sequence chi according to commodity browsinginformation of a user u; s2, determining the window time Wt of the user according to the click frequency of the user u; s3, obtaining the user novelty through calculation, wherein the probability thatthe user u selects a new commodity at the moment t is predicted according to the behavior historical record of the user u when the user selects to start to cut off the moment t; and S4, according tothe obtained user novelty, recommending commodities or commodity combinations meeting the user novelty at the moment t to the user. According to the online commodity recommendation method, the user novelty is calculated by introducing psychological indicator factors of the user for the openness degree of new and old commodities, and commodity / commodity combination recommendation is performed on the user according to the user novelty, so that the online commodity recommendation method can improve the accuracy of personalized recommendation, and more economic benefits are created for an e-commerce platform.

Description

technical field [0001] The invention relates to a personalized recommendation system of an e-commerce platform, in particular to an online product recommendation method based on user novelty. Background technique [0002] With the improvement of social productivity, new consumer products are constantly pouring into the market, and the rapid development of e-commerce platforms has brought new consumption drivers. According to the latest research in 2020, online sales channel revenue currently accounts for 12% of total global retail sales; in the next five years, its growth rate will be four times that of physical transactions. Such a high-speed growth rate has brought a golden age of consumption dividends to the e-commerce platform, and it also faces an increasingly fierce competition crisis. [0003] Obviously, search technology can effectively filter information and help users find their favorite products, but it cannot promote the growth of new consumption, and recommenda...

Claims

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Application Information

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IPC IPC(8): G06Q30/06G06N20/00
CPCG06Q30/0631G06N20/00
Inventor 马梦伶江勇李丽黄维
Owner SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
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