Method for discovering key person in a dynamic large-scale social network

A key person and social network technology, applied in the field of key person discovery, can solve problems such as the dynamics of social networks and the nature of big data, and the high time complexity of algorithms

Active Publication Date: 2017-05-31
BEIHANG UNIV
View PDF5 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The above work on social network analysis and key person discovery does not take into account the dy

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
  • Method for discovering key person in a dynamic large-scale social network
  • Method for discovering key person in a dynamic large-scale social network
  • Method for discovering key person in a dynamic large-scale social network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0028] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0029] The present invention proposes a method for discovering key figures in a dynamic large-scale social network. key person. The dynamic large-scale social network refers to a complex network in real life, such as a social network composed of all users of Sina Weibo. The network data scale is huge, the structure is extremely complex, and the relationship between people is changing dynamically. The aforementioned key person refers to a person who can play a key role in the network. For example, a big V on Sina Weibo can influence his fans and play a key role in disseminating information.

[0030]The method proposed in the present invention for finding key figures in a dynamic large-scale social network mainly includes four processes: (1) node label and parameter selection; (2) local network extraction and mutual influence calculation between n

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 method for discovering key person in a dynamic large-scale social network, which belongs to the field of data mining and social network analysis. The method first performs node labeling and parameter K selection, and then calculates the mutual influence between the nodes in a certain localized network. The importance index of the single node is calculated and the key person is found according to the task type. The method for discovering key person in a dynamic large-scale social network puts forward a concept of universal influence, and gives a formula of calculating the mutual influence between the nodes in a certain localized network and the importance index, and has advantages in the large-scale dynamic social network. According to the difference of the task type, the method can have different result processing strategies, and can adjust the parameter K to balance the time complexity and accuracy.

Description

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

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
Owner BEIHANG 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