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Collaborative filtering recommendation method based on user interest groups

A technology of collaborative filtering recommendation and user interest, applied in the field of recommendation based on collaborative filtering, it can solve the problem of low accuracy and achieve the effect of improving accuracy

Inactive Publication Date: 2013-09-04
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the shortcomings of the low accuracy of existing collaborative filtering recommendation methods, the present invention proposes a collaborative filtering recommendation method based on user interest grouping to provide users with more accurate and relevant items

Method used

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  • Collaborative filtering recommendation method based on user interest groups
  • Collaborative filtering recommendation method based on user interest groups
  • Collaborative filtering recommendation method based on user interest groups

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Embodiment Construction

[0025] With reference to accompanying drawing, further illustrate the present invention:

[0026] A collaborative filtering recommendation method based on user interest grouping, the method includes the following steps:

[0027] 1. After obtaining the relationship data between users and items, perform the following steps on these data:

[0028] 1) Standardize the data on the relationship between users and items;

[0029] 2) Perform dimension reduction processing, mapping users and items to a low-dimensional space;

[0030] 3) Use the clustering method to divide users and items into multiple different groups;

[0031] 4) Use any collaborative filtering method to obtain the predicted value on each group;

[0032] 5) Merge the predicted values ​​of different groups and make recommendations to users.

[0033] In step 1), the data of the relationship between the user and the item is expressed in a normalized manner:

[0034] 1) Express the relationship between users and items ...

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Abstract

Provided is a collaborative filtering recommendation method based on user interest groups. After relational data between users and objects are acquired, following operation is conducted aiming at the data. First the data are subjected to standardization expression, then the data are subjected to dimension reduction processing, the users and the objects are mapped to a common dimension reduction space, then a clustering method is utilized to divide the users and the objects which are subjected to dimension reduction into different interest groups, the collaborative filtering recommendation method is utilized on the basis of each group to conduct prediction, and finally prediction values of different groups are combined and recommended for the users. The method has that advantage that the relation between the users and the objects can be described intensively, the interest groups of the users can be found quickly, and accuracy of the collaborative filtering recommendation method is improved.

Description

technical field [0001] The invention relates to the technical field of personalized recommendation methods, in particular to a recommendation method based on collaborative filtering. Background technique [0002] Now we are always enjoying the convenience brought by the rapid development of the Internet. Online music playback and online shopping have enriched our lives, but at the same time we are also in an era of information explosion. According to the data released by Taobao in 2011, the number of its online products exceeds 800 million, which brings troubles for users to find suitable products. The recommendation system alleviates this problem to a large extent. An accurate recommendation algorithm can not only bring convenience to users, but also increase the revenue of the website. The quality of the recommendation method greatly affects the user experience, and how to improve the accuracy of the recommendation algorithm has become a hot research topic in recent years...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06Q30/02
Inventor 卜佳俊陈纯王灿徐斌秦绪震吴晓凡谭树龙
Owner ZHEJIANG UNIV