Two-stage inspiration-based social network influence maximization problem solving method

A technology of maximizing influence and social network, applied in the field of social network analysis, can solve the problems of low algorithm precision, poor adaptability, large influence, etc., and achieve the effect of high computational complexity

Inactive Publication Date: 2016-11-09
JIANGXI UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

In viral marketing on social networks, the key issue is: how to find a set of marketing nodes at a relatively low cost, and finally maximize the impact on the entire network, which is also called the impact maximization problem.
Among them, the efficiency of the heuristic algorithm is better than the greedy algorithm, but most of the existing heuristic algorithms focus on a single heuristic factor, such as degree, betweenness, etc., without considering the overall structure of the network, making the algorithm less accurate and less adaptable

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  • Two-stage inspiration-based social network influence maximization problem solving method
  • Two-stage inspiration-based social network influence maximization problem solving method
  • Two-stage inspiration-based social network influence maximization problem solving method

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Embodiment Construction

[0046] The present invention will be further described below in conjunction with implementation examples and accompanying drawings.

[0047] The relevant knowledge involved in this method is as follows:

[0048] The influence maximization algorithm is to find a node set composed of k nodes under a certain propagation model, and finally make the influence of this set in the entire network to be maximized.

[0049] The propagation model involved in the present invention is a linear threshold model, which is introduced as follows:

[0050] The linear threshold model and the independent cascade model are two basic models in the influence maximization problem. The linear threshold model has the characteristic of accumulating influence, which is also the premise that this civilization can divide the influence maximization algorithm into two processes. In the linear threshold model, there are only two states for each node: active and inactive, and each node can only be activated once....

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Abstract

The invention discloses a two-stage inspiration-based social network influence maximization problem solving method, and belongs to the field of social network analysis. The method comprises the following processing procedure of: dividing the whole process of an influence maximization algorithm into two stages by utilizing accumulation characteristics of a liner threshold value model: (1) a degree discounting inspiration stage: selecting a seed node with the maximum degree by using a degree discounting strategy, carrying out node activation in the whole network by utilizing the seed node and accumulating the influence of the nodes; and (2) an influence inspiration stage: selecting a node with the maximum influence as a target node and carrying out node activation by utilizing the target node. In order to improve the solution speed of the algorithm, a calculation method for approximately evaluating the node influence is designed at the influence inspiration stage. The method disclosed by the invention can be used for effectively and rapidly mining the initial seed nodes in social networks and effectively solving the influence maximization problem in the social networks, and can be applied to the field of marketing, public opinion monitoring and advertising.

Description

technical field [0001] The invention relates to the field of social network analysis, in particular to a method for solving the social network influence maximization problem based on two-stage heuristics. Background technique [0002] A social network is a social network composed of individuals in the network. This individual can be any identification code appearing in the network that can distinguish others, such as an individual, an organization, or a user name. In recent years, the rise of various large-scale online social networks has produced massive network data, which makes it possible to study various phenomena in human society on a global scale. In order to better mine hidden information in social networks, researchers have carried out various social network analysis. Later, it was found that the hobbies and behaviors of individuals or organizations in social networks often affect the surrounding individuals or organizations, which provided an opportunity for "vira...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q50/00
CPCG06Q50/01
Inventor 杨书新刘成辉
Owner JIANGXI UNIV OF SCI & TECH
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