Network link prediction method based on multiple semantic influences of multiple neighbor nodes

A technology of neighbor nodes and prediction methods, applied in the field of social computing, which can solve problems such as inability to obtain

Active Publication Date: 2020-02-28
TIANJIN UNIV
View PDF7 Cites 14 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in traditional methods, a user node has only a constant influence score, and when a user node influences different neighbor nodes around him / her, it cannot get nuanced influence

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Network link prediction method based on multiple semantic influences of multiple neighbor nodes
  • Network link prediction method based on multiple semantic influences of multiple neighbor nodes
  • Network link prediction method based on multiple semantic influences of multiple neighbor nodes

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0066] The technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments, and the described specific embodiments are only for explaining the present invention, and are not intended to limit the present invention.

[0067] The network link prediction method based on multiple semantic influences of multiple neighbor nodes proposed by the present invention includes three steps: data analysis, model training and prediction analysis.

[0068] 1. Data analysis: It is used to analyze user behavior and user relationship data in social networks, and analyze relevant attribute vectors from user interest attributes and user friend attributes respectively; obtain node interest characteristics and network structure characteristics. The social network is expressed as G=(N, E, S), and the nodes in the social network all have text attributes, which contain interest information. Among them, N={u 1 ,...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a network link prediction method based on multiple semantic influences of multiple neighbor nodes, relates to data mining and topological structure analysis, and belongs to a research problem in the field of social computing. The method comprises the following steps: data analysis: analyzing node interest characteristics and network structure characteristics based on node behaviors and node relationship data in a social network; and model training: obtaining an embedded vector of each node by the model in combination with multiple semantic influences of multiple neighbor nodes; predictive analysis: measuring the probability of existence of friend links by using the similarity between the embedded vectors of the node pairs. According to the method, the constant influence scores of the neighbors are not used, and the special semantic influence of each neighbor on the node is simulated. Local-level and global-level semantic influences of neighbor nodes in network embedding training are jointly simulated, and a joint embedding vector based on the semantic influences of all the neighbor nodes is trained for each node.

Description

technical field [0001] The invention relates to data mining and topological structure analysis, and belongs to a research problem in the field of social computing. A network link prediction method combining multiple semantic influences of multiple neighbor nodes is proposed. Background technique [0002] Among many tasks in social networks, link prediction is very important. The task consists of two kinds of problems: the first is to infer possible future social links in the social network, and the other is to reconstruct the existing links that are missing in the current snapshot of the social network. The aim of the present invention is to solve the latter, namely to reconstruct missing links in social networks. [0003] To achieve link prediction, the topology information of the network is widely used in traditional link prediction methods, which are called topology-based methods. Topology-based link prediction only considers the structural information of social networ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/2458G06F16/28G06F40/30G06N3/04G06N3/08G06Q50/00
CPCG06F16/2465G06F16/288G06N3/08G06Q50/01G06N3/048G06N3/045Y02D30/70
Inventor 王博宋美贤胡清华
Owner TIANJIN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap