Personalized commodity recommendation method

A commodity recommendation and commodity technology, applied in the direction of buying and selling/lease transactions, instruments, calculations, etc., can solve the problem of low recommendation accuracy, achieve high recommendation accuracy, improve accuracy, and improve accuracy

Active Publication Date: 2019-06-18
HUAZHONG UNIV OF SCI & TECH +2
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The present invention provides a personalized product recommendation meth

Method used

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  • Personalized commodity recommendation method
  • Personalized commodity recommendation method
  • Personalized commodity recommendation method

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0057] Example one

[0058] A personalized product recommendation method 100, such as figure 1 Shown, including:

[0059] Step 110: Receive a product search instruction from a user in need, where the instruction includes a product category;

[0060] Step 120: Based on the stored information in the database, determine whether the user in need has been classified, if yes, execute step 130, if not, execute step 160;

[0061] Step 130: Calculate multi-dimensional average label information preferred by the user in need based on the first multi-dimensional label information of multiple commodities interacting with the commodity category by the user in need;

[0062] Step 140: Turn on the recommendation model of the user cluster to which the demanded user belongs, and the recommendation model is based on the multi-dimensional average tag information to calculate and output the first multi-dimensional attribute information;

[0063] Step 150: Calculate the distance between the first multi-dimens...

Example Embodiment

[0124] Example two

[0125] A storage medium in which instructions are stored. When the instructions are read by a computer, the computer executes the personalized product recommendation method as in the first embodiment.

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Abstract

The invention relates to a personalized commodity recommendation method. The method comprises the steps of receiving a commodity search instruction of a user; If the users are classified, calculatingmulti-dimensional average label information preferred by the users, wherein a recommendation model of the users calculates first multi-dimensional attribute information based on the multi-dimensionalaverage label information, calculates the distance between the first multi-dimensional attribute information and second multi-dimensional attribute information of each commodity in the commodity category, and pushes the commodities with the smaller distance to the users; Otherwise, calculating first multi-dimensional average attribute information based on the second multi-dimensional attribute information of the plurality of commodities, and determining a recommendation model suitable for the user based on the first multi-dimensional average attribute information and the recommendation model of each type of users. According to the recommendation method provided by the invention, firstly, users are clustered, and multi-dimensional commodity label information and commodity attribute information are utilized, so that the recommendation accuracy is high; Besides, when the user is a new user, a recommendation model of the new user is formed by utilizing an existing recommendation model through attention transfer learning, so that the cold start problem is solved.

Description

technical field [0001] The invention relates to the technical field of data mining, in particular to a method for recommending personalized commodities. Background technique [0002] With the continuous development of network technology, in today's era of information overload, both as information consumers and information producers have encountered great challenges: information consumers need to find the information they are interested in from the massive amount of information; Information producers need to make their information stand out and attract users' attention. The personalized recommendation method can solve the above problems very well. At present, the main personalized recommendation methods mainly include content-based recommendation methods and collaborative filtering recommendation methods. However, these methods generally have problems such as low accuracy and cold start. Contents of the invention [0003] The present invention provides a method for recomm...

Claims

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Application Information

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IPC IPC(8): G06Q30/06G06K9/62
Inventor 李国徽潘鹏李剑军杜俊博魏明胡志勇徐萍石才谭敏
Owner HUAZHONG UNIV OF SCI & TECH
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