Commodity recommendation method and device

A product recommendation and product technology, applied in the computer field, can solve the problems of reducing the efficiency of the recommendation system and the information redundancy of the product.

Pending Publication Date: 2020-04-07
TSINGHUA UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Among them, the diversity directly affects the user's perception of the recommendation results, and the lack of diversity of the recommendation results makes the products in the recommendation list appear redundant information, which reduces the effectiveness of the recommendation system

Method used

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  • Commodity recommendation method and device
  • Commodity recommendation method and device
  • Commodity recommendation method and device

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Embodiment Construction

[0041] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0042] figure 1 The flow chart of the product recommendation method provided by the embodiment of the present invention, such as figure 1 As shown, the method includes:

[0043] S1. Input the target user into the trained recommendation system to obtain a set of candidate commodities, the set of candidate commodities includes several candidate co...

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Abstract

The embodiment of the invention provides a commodity recommendation method and device. The commodity recommendation method comprises the steps: inputting a target user into a trained recommendation system, and obtaining a candidate commodity set; reordering each candidate commodity in the candidate commodity set based on a nearest neighbor search algorithm according to the target user representation vector and the target commodity representation vector, and taking a plurality of candidate commodities sorted in the top as optimal recommended commodities; and recommending all the optimal recommended commodities to the user. The commodity recommendation method and device generate the target user representation vector and the target commodity representation vector according to the similarity between the target user and each commodity, based on the recommendation system constructed by the graph neural network, so that the diversity of the candidate commodities is improved, and the diversityof the best recommended commodities is improved, and the commodity with the maximum probability is recommended to the user through the commodity recall stage, and the recommendation accuracy is improved.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a commodity recommendation method and device. Background technique [0002] Recommender system is an effective algorithm to solve the problem of information overload. Through the correlation modeling of user interaction history data and various features, the recommendation system can filter out products that meet the user's interests from a large number of candidate products. [0003] With the widespread deployment of recommendation systems in various Internet applications such as e-commerce, online news, and multimedia entertainment, the user experience measurement of recommendation systems has also expanded from a single accuracy index to include accuracy, diversity, novelty, and fairness. Comprehensive evaluation indicators of multiple dimensions such as sex. [0004] Among them, the diversity directly affects the user's perception of the recommendation results, an...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/06G06K9/62G06F16/9535G06F16/9538
CPCG06Q30/0631G06Q30/0629G06F16/9535G06F16/9538G06F18/24147
Inventor 李勇郑瑜卢中县金德鹏周亮张良伦
Owner TSINGHUA UNIV
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