Social network friend recommending method based on multiple personal characteristic hybrid architecture

A technology for social network and friend recommendation, applied in the field of social network friend recommendation based on a hybrid architecture of multiple personalized features, can solve the problem of ignoring the interaction information of users' personalized features, and achieve the effect of improving the accuracy rate

A technology for social network and friend recommendation, applied in the field of social network friend recommendation based on a hybrid architecture of multiple personalized features, can solve the problem of ignoring the interaction information of users' personalized features, and achieve the effect of improving the accuracy rate

CN107526850AInactive Publication Date: 2017-12-29YANSHAN UNIV
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  • Social network friend recommending method based on multiple personal characteristic hybrid architecture
  • Social network friend recommending method based on multiple personal characteristic hybrid architecture
  • Social network friend recommending method based on multiple personal characteristic hybrid architecture

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0052] 1. The embodiment of the present invention takes personalized node characteristics: interest degree, interest activity, and the node sorting method takes the weighted average method as an example, figure 1 Shown is a schematic diagram of the hybrid architecture based on multiple personalized features of the present invention, and its implementation steps are as follows:

[0053] First, define the intimacy feature and construct the intimacy probability transition matrix;

[0054] Second, introduce the random walk algorithm to calculate the interaction degree score value between users;

[0055] Third, define and extract user node features on the basis of defining network feature intimacy, and construct a multi-feature transfer matrix;

[0056] Fourth, introduce the weighted average method to calculate the similarity value of the extracted node features and sort them;

[0057] Fifth, run the random walk model and recommend to target users according to the obtained recommen...

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Abstract

The invention discloses a social network friend recommending method based on multiple personal characteristic hybrid architecture. The method comprises: defining intimacy degree characteristics according to attribute information of users in conjunction with inter-user interactive information, constructing an intimacy degree probability transfer matrix, and introducing a random walk model to calculate inter-user interaction degree scores; on this basis, defining personal node characteristics of the users, using a weighted average method to assign different weights to the characteristics, and using a random walk algorithm to obtain a Top-N recommendation list for recommending. The method of the invention has the advantages that attribute information and interactive information of users are fully considered, interest characteristics of the users are considered, behavior characteristics of the users in a social network are also considered, real friend needs of the users can be truly reflected through these personal network characteristics and node characteristics, and friend recommending accuracy is greatly improved.

Description

technical field [0001] The invention relates to a personalized friend recommendation model in a social network, in particular to a social network friend recommendation method based on a mixed architecture of multiple personalized features. This method combines the attribute information of users and the interaction information between users to define the characteristics of intimacy, construct the probability transition matrix of intimacy, and introduce the random walk model to calculate the score value of the interaction degree between users. On this basis, define the user's personalized node characteristics, use the weighted average method to assign different weights to them, and finally use the random walk algorithm to get the Top-N recommendation list for recommendation. Based on this, a unified personalized friend recommendation model is constructed to realize personalized friend recommendation. Background technique [0002] Recommendation is an effective way to search f...

Claims

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Application Information

Patent Timeline
29 Dec 2017
Publication
CN107526850A
IPC
G06F17/30; G06Q50/00
CPC
G06F16/9535; G06Q50/01
Inventors
宫继兵; 高小霞