Method for discovering community structure oriented to directed-weighting network

Abstract

The invention provides a method for discovering a community structure oriented to a directed-weighting network. The method comprises the following steps: constructing the directed-weighting network based on the inter-node social relationship weight and direction; converting the directed-weighting network into an undirected-weighting network; initializing a network topology, and constructing a weight matrix; normalizing the matrix and calculating community discovery decision factors which specifically comprise node liveness, community relationship intensity, community density and community coupling degree; partitioning the network community based on the community discovery decision factors. The method can be used for rapidly discovering and construction the network community under a mobile, hetergeneous and dynamic environment, providing credible service links for users, realizing mobile sensing service credibility interaction, further improving the mobile sensing service and finally providing high-quality, diversified and customized group intelligent sensing service for the user.

Description

【Technical field】 [0001] The invention belongs to the field of crowd-sensing services, and in particular relates to a community structure discovery method for directed-weighted networks. 【Background technique】 [0002] The emergence of social networks has broadened the boundaries of the network, making it more closely integrated with real life. At the same time, it has also endowed virtual networks with more characteristics and characteristics that are very similar to real social environments. The existence of community structures is a typical example. . In a real social network, each of us has our own social attributes, such as occupation, place of residence, or kinship with others, etc. People with the same social attributes will establish closer social relationships. We call this phenomenon that the social relationship value between members of the group is much greater than the social relationship value between members in the group and members outside the group as the ex...

AI Technical Summary

Problems solved by technology

However, most of the algorithms are researched based on the social network of undirected and unweighted graphs or undirected weighted graphs, while the network drawn by the perception information actually obtained through terminal perception is a directed weighted graph, which is mature in this area. Algorithms are less

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