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Device and method for recommending personalized information and information processing system

An information processing system and information recommendation technology, applied in the field of information processing system and personalized information recommendation, can solve the problems of difficult to accurately reflect the similarity of users or items, easy to generate data sparsity, etc., to achieve enhanced reliability and accurate reflection. , the effect of improving the accuracy

Active Publication Date: 2013-02-06
TENCENT TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The embodiment of the present invention provides a method for personalized information recommendation, which aims to solve the problems that the existing technology is prone to data sparsity and difficult to accurately reflect the similarity relationship between users or items

Method used

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  • Device and method for recommending personalized information and information processing system
  • Device and method for recommending personalized information and information processing system
  • Device and method for recommending personalized information and information processing system

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0026] figure 1 The implementation flow of the personalized information recommendation method provided by Embodiment 1 of the present invention is shown, and the process of the method is described in detail as follows:

[0027] In step S101, interaction records between SNS users and usage records of items by SNS users are obtained.

[0028] In this embodiment, social network services (Social Networking Services, SNS) are referred to as social networks for short. The social network server collects and stores the interaction records of SNS users through social network tools, and the recommendation system obtains the interaction records between SNS users from the SNS server.

[0029] Wherein, the social networking tools include instant messaging tools (such as QQ, MSN, etc.) and friend-making communities (such as Facebook, Twitter, etc.) and other network making friends or communication platforms that include friend relationships. The interaction record includes information suc...

Embodiment 2

[0045] figure 2 It shows the implementation flow of the explicit network map comment information method provided by Embodiment 2 of the present invention, and the method process is described in detail as follows:

[0046] In step S201, interaction records between SNS users and usage records of items by SNS users are obtained.

[0047] In step S202, according to the interaction records, the similarity between SNS users is calculated, and user similarity groups are divided according to the calculated similarity.

[0048] In step S203, according to the usage record, the rating value of the item by the SNS user is calculated.

[0049] In step S204, the rating value of the target user for the item is predicted according to the rating value of the item used by other users in the user similar group.

[0050] In step S205, the top N items with the highest predicted ratings are recommended to the target user.

[0051] In this embodiment, for the specific implementation process of s...

Embodiment 3

[0057] image 3 The composition structure of the device for recommending personalized information provided by the third embodiment of the present invention is shown, and for the convenience of description, only the parts related to the embodiment of the present invention are shown.

[0058] The personalized information recommendation device can be a software unit, a hardware unit, or a combination of software and hardware running in the information processing system, or it can be integrated into these information processing systems as an independent pendant or run on the applications of these information processing systems system.

[0059] The personalized information recommendation device includes an information acquisition unit 31 , a similarity calculation unit 32 , a score value calculation unit 33 , a score value prediction unit 34 and an information recommendation unit 35 . Among them, the specific functions of each unit are as follows:

[0060] An information acquisit...

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Abstract

The invention is applicable to the field of information processing and provides a device and a method for recommending personalized information and an information processing system. The method includes: acquiring interaction records of SNS (social network site) users and article usage records of the SNS users; calculating similarity among the SNS users according to the interaction records, and dividing the SNS users into similarity groups according to the similarity; calculating grades, given by the SNS users, of articles according to the article usage records; predicting grades, given by target users, of the articles according to grades, given by other users in the similarity groups, of the articles; and recommending top N highly-graded articles to the target users. Accuracy and credibility of recommending results are improved effectively, and the recommended personalized information has greater reference value for users.

Description

technical field [0001] The invention belongs to the field of information processing, and in particular relates to a method, device and information processing system for personalized information recommendation. Background technique [0002] Collaborative filtering technology is one of the most widely used personalized recommendation technologies. The existing collaborative filtering technology mainly recommends based on the user similarity relationship or item similarity relationship generated by the recommended item itself. Relationships between items, and finally use these relationships for recommendation. [0003] However, since the user historical data information utilized by the existing technology only comes from the recommended item itself, it is easy to cause the data in the user-item rating matrix to be sparse, which affects the accuracy of the recommendation results. In particular, it is difficult to accurately reflect the similarity relationship between users or ...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06Q30/02H04L29/08
Inventor 贺鹏程周杰龙杨志峰
Owner TENCENT TECH (SHENZHEN) CO LTD
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