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Multi-dimensional user collaborative filtering recommendation method combined with association rules

A collaborative filtering recommendation, multi-dimensional technology, applied in data processing applications, business, instruments, etc., can solve problems that affect user decision-making, achieve good expansion, improve accuracy, and strong applicability

Inactive Publication Date: 2018-12-07
CHENGDU UNIV OF INFORMATION TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

And these contextual information will also greatly affect the user's decision-making

Method used

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  • Multi-dimensional user collaborative filtering recommendation method combined with association rules
  • Multi-dimensional user collaborative filtering recommendation method combined with association rules
  • Multi-dimensional user collaborative filtering recommendation method combined with association rules

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Experimental program
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Embodiment Construction

[0038] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0039] definition:

[0040] (1) User: It is represented by u in the text, which generally refers to the website or all users of the website.

[0041] (2) Target user: It is represented by a in the text, indicating the user who needs to make product recommendations for it.

[0042] (3) Neighboring users: denoted by u' in the text, indicating other users with similar interests to the target user.

[0043] Step 1: Collect the user's purchase record, which contains the context information of the user's purchase, and generate a user-scoring matrix containing the context information.

[0044] Step 2: Calculate user similarity

[0045]

[0046] Among them, s a,u,c Indicates the similarity value between the target user a and user u in the context of c, I a Represents the collection of items rated by the target user a, I u Represents the colle...

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Abstract

The invention relates to a multi-dimensional user collaborative filtering recommendation method combined with association rules. The method comprises steps that firstly, context dimensions are fused into the user collaborative filtering algorithm, and user similarity and the commodity prediction score are calculated under influence of context factors, moreover, the FP-growth association rule algorithm is utilized to mine a frequent item set not included in the commodity purchase record of a target user, and the mining result is fused into a recommendation list. The method is advantaged in thatinfluence of the context dimension factors is considered, and accuracy of a recommendation system can be improved.

Description

technical field [0001] The invention relates to the technical field of recommendation algorithms, in particular to a multi-dimensional user collaborative filtering recommendation method combined with association rules. Background technique [0002] With the advent of the web2.0 era, the Internet has entered the era of data explosion. While massive data brings richness to users, it also drowns out effective data. The recommendation system can analyze the user's historical purchase behavior and other global information, and recommend products that may be of interest to the user. It helps users quickly locate the points of interest among massive commodities, improves the efficiency of information matching, and also makes merchants more targeted when placing advertisements, which helps to achieve a win-win situation between users and merchants. [0003] With the development of communication technology, the data traffic that the mobile terminal can carry is increasing, and user...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02G06Q30/06
CPCG06Q30/0255G06Q30/0631
Inventor 李彤岩徐嘉临肖翔
Owner CHENGDU UNIV OF INFORMATION TECH