Method for mining cohesion subgraphs in bipartite graph network based on neighbor number and edge strength

A bipartite graph network and a bipartite graph technology, applied in the direction of electrical digital data processing, other database retrieval, other database indexing, etc., can solve problems such as the number of nodes that cannot be calculated, and the participation of nodes that cannot be parameterized, so as to facilitate analysis , the effect of reducing the search space

Inactive Publication Date: 2020-09-18
ZHEJIANG GONGSHANG UNIVERSITY
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Problems solved by technology

Another disadvantage of the ω-bipartite truss model is that it cannot parameterize the participation of nodes,

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  • Method for mining cohesion subgraphs in bipartite graph network based on neighbor number and edge strength
  • Method for mining cohesion subgraphs in bipartite graph network based on neighbor number and edge strength

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[0031] In order to make the above objects, features and advantages of the present invention more comprehensible, specific implementations of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0032] In the following description, a lot of specific details are set forth in order to fully understand the present invention, but the present invention can also be implemented in other ways different from those described here, and those skilled in the art can do it without departing from the meaning of the present invention. By analogy, the present invention is therefore not limited to the specific examples disclosed below.

[0033] This application proposes a method for mining cohesive subgraphs in bipartite graph networks based on the number of neighbors and edge strength, which includes two novel pruning strategies and efficient mining of (α,β,ω)-kernel models algorithm. The implementation process of each part is described in de...

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Abstract

The invention discloses a method for mining cohesion subgraphs in a bipartite graph network based on neighbor number and edge strength. In order to find a cohesion sub-graph simultaneously meeting theneighbor number and the edge strength, a new cohesion sub-graph model is provided on a bipartite graph network, namely a (alpha, beta, omega)-kernel model; two conditions are met: each node in the subgraph has enough neighbors with connected strong edges; wherein the strong edge represents that the edge is contained in at least omega butterflies, enough neighbors connected with the strong edge represent that at least alpha neighbors connected with the strong edge of the node exist in the upper layer of the bipartite graph, and at least beta neighbors connected with the strong edge of the nodeexist in the lower layer of the bipartite graph; wherein the sub-graphs are great. Considering the time complexity of calculating the model, the invention provides a new pruning strategy, so that thesearch space is reduced more effectively. Meanwhile, an efficient (alpha, beta, omega)-kernel model calculation algorithm is developed in combination with a new pruning strategy, so that the (alpha,beta, omega)-kernel model can be quickly found in the large bipartite graph network.

Description

technical field [0001] The invention belongs to the technical field of multimedia data mining, and in particular relates to a method for mining cohesive subgraphs in a bipartite graph network based on the number of neighbors and edge strength. Background technique [0002] Many practical applications across different types of entities can be modeled as bipartite graphs, such as customer-product networks, author-paper collaboration networks, etc. The bipartite graph G(U,V,E) consists of two types of nodes, namely U and V, where nodes of the same type do not intersect, that is, only one of the two endpoints of an edge in E exists in U, and the other present in V. [0003] With the proliferation of bipartite graphs in various research fields, scholars have conducted many studies to analyze the properties of bipartite graphs. As a fundamental problem in graph analysis, the problem of mining cohesive subgraphs has been extensively studied. For bipartite graphs, researchers hav...

Claims

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Application Information

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IPC IPC(8): G06F16/901G06F16/9035
CPCG06F16/9024G06F16/9035
Inventor 陈晨杨镐朱秋雨张梦琪郑佳红王潇杨
Owner ZHEJIANG GONGSHANG UNIVERSITY
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