Parallel Enumeration Method of Maximum Bipartite Groups Based on Sparse Bipartite Graph

A bipartite graph and grouping technology, applied in instruments, database indexing, computing, etc., can solve problems such as low computing efficiency, and achieve the effect of improving computing efficiency, reducing memory pressure, and efficiently assigning initialization tasks.

Inactive Publication Date: 2021-08-31
SHENZHEN UNIV
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Problems solved by technology

[0004] This application provides a parallel enumeration method for extremely large bipartite groups based on sparse bipartite graphs, which can solve the technical problem of low computational efficiency in the prior art for solving MBE problems

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  • Parallel Enumeration Method of Maximum Bipartite Groups Based on Sparse Bipartite Graph
  • Parallel Enumeration Method of Maximum Bipartite Groups Based on Sparse Bipartite Graph
  • Parallel Enumeration Method of Maximum Bipartite Groups Based on Sparse Bipartite Graph

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[0028] In order to make the purpose, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described The embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts belong to the protection scope of the present invention.

[0029] Currently, graph models, as an abstraction of complex relationships in data, have been widely used in various fields, such as social networks, recommendation systems, and bioinformatics. Such graph data contains many dense substructures. From these graphs, finding these dense substructures, such as clique, biclique, and k-cores, is a ...

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Abstract

The invention discloses a parallel enumeration method of extremely large bipartite groups based on a sparse bipartite graph. Compared with the prior art, the invention adopts a parallel computing method, which can enable parallel computing of various computing tasks, including uniform initialization tasks Assignment and efficient task migration, as well as de-redundancy operations on the amount of information of a single task, so that redundant and repeated information is stored in a common area, and each task will only be queried and obtained when it is executed. , which not only reduces the pressure on the memory, but also speeds up the task migration, and can effectively improve the computing efficiency when solving the MBE problem.

Description

technical field [0001] The invention relates to the technical field of graph data mining, in particular to a parallel enumeration method for extremely large dichotomous groups based on a sparse bipartite graph. Background technique [0002] In recent years, the MBE (maximal biclique enumeration) problem based on bipartite graphs is one of the research hotspots in the field of graph data mining. MBE problems can be applied to the discovery and analysis of biological phylogenetic trees, protein interaction network structures, product recommendations, and character interest analysis. [0003] At present, to solve the MBE problem on the bipartite graph, the serial calculation method is generally adopted. This calculation method cannot make full use of hardware resources, and the calculation efficiency is low. Contents of the invention [0004] The present application provides a method for parallel enumeration of extremely large bipartite groups based on a sparse bipartite gra...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/22G06F16/2458
CPCG06F16/2246G06F16/2465
Inventor 何宇李荣华毛睿荣钰王毅廖好
Owner SHENZHEN UNIV
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