User group correlation degree-based personalized recommendation method and system

A recommendation method and recommendation system technology, applied in the field of Internet communication, can solve problems such as error in recommendation results, and achieve the effect of improving accuracy

Active Publication Date: 2013-05-01
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0012] In view of this, the embodiment of the present invention provides a personalized recommendation method and system based on user group relevance, which

Method used

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  • User group correlation degree-based personalized recommendation method and system
  • User group correlation degree-based personalized recommendation method and system
  • User group correlation degree-based personalized recommendation method and system

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Embodiment 1

[0042] Figure 4 It is a method flowchart of a personalized recommendation method based on user group relevance provided by the first embodiment of the present invention, which includes Step A to Step E.

[0043] Step A, using a clustering algorithm to cluster the users;

[0044] Step B. Determine the distance between the target user and the cluster edge. When the distance is greater than a given threshold, execute step C. Otherwise:

[0045] B-1. Calculate the degree of association between the cluster where the target user is located and other clusters;

[0046] B-2. Merge the first r clusters most relevant to the cluster where the user is located;

[0047] B-3. ​​Find n nearest neighbors in the merged cluster, and then execute step D;

[0048] Step C. Find n nearest neighbors in the cluster where the target user is located;

[0049] Step D. Predict the user's ratings on related products based on the ratings of the nearest neighbors on the products.

[0050] Step E. Sele...

Embodiment 2

[0067] Figure 9 It is a schematic structural diagram of a personalized recommendation system 100 based on user group relevance provided by the second embodiment of the present invention, including a clustering module 11 , a judgment module 12 , a search module 13 , a score prediction module 14 , and a recommendation module 15 .

[0068] The clustering module 11 is used for clustering users using a clustering algorithm.

[0069] The judging module 12 is used to judge the distance between the target user and the cluster edge. When the distance is greater than a given threshold, the search module 13 is executed; Wherein the degree of association calculation unit 131 is used to calculate the degree of association between the cluster where the target user is located and other clusters; the cluster merging unit 132 is used to merge the first r clusters most relevant to the cluster where the user is located; the search subunit 133 It is used to find n nearest neighbors in the merge...

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Abstract

The invention relates to the field of internet communication, and discloses a user group correlation degree-based personalized recommendation method, which comprises the following steps of: A, clustering users by using a clustering algorithm; B, judging distance from a target user to a cluster edge, executing a step C when the distance is greater than a given threshold value, otherwise executing B-1, calculating correlation degree between a cluster of the target user and other clusters, B-2, combining previous r clusters related with the cluster of the user, B-3, searching n closest neighbors in the combined cluster, and further executing a step D; C, searching n closest neighbors in the cluster of the target user; D, predicting a grading value of a related product according to grade of the closest neighbor on the product; and E, selecting the previous m products to be recommended to the user according to the level of a predicted grading value. The invention also discloses a user group correlation degree-based personalized recommendation system. According to the method and the system, the accuracy for personalized recommendation can be effectively improved.

Description

technical field [0001] The invention belongs to the field of Internet communication, and in particular relates to a personalized recommendation method and system based on user group relevance. Background technique [0002] The recommendation system is an intelligent system that analyzes the user's interests and hobbies based on the user's historical behavior records, such as commodity purchase records, network click logs, and recommends corresponding products or information to them based on the analysis results. [0003] Collaborative filtering is the most commonly used and most effective algorithm in the current recommendation system. The starting point of the algorithm is users with the same or similar interest preferences, and the evaluation of products is similar. There are two main steps: 1. Find n other users who are most similar to the target user, which are called nearest neighbors; 2. Predict the possible rating value of the target user for the product according to ...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 高明黄哲学
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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