Multi-domain network community discovery system fusing discrete time quantum walk

Abstract

The invention provides a multi-domain network community discovery system fusing discrete time quantum migration. The multi-domain network community discovery system comprises a code construction module, a quantum replacement module, a migration module, a community optimization module and an evaluation index module, the data output end of the code construction module is connected with the data input end of the quantum permutation module, the data output end of the quantum permutation module is connected with the data input end of the migration module, and the data output end of the migration module is connected with the data input end of the community optimization module. The data output end of the community optimization module is connected with the data input end of the evaluation index module. According to the invention, the community in the multi-domain network can be quickly and efficiently detected.

Description

Technical field [0001] The present invention relates to a community discovery technology, and in particular, there is a multi-domain network community discovery system that fused discrete time quantum swimming. Background technique [0002] "People are gathered, people with populations", people with similar properties tend to form intimate small circles, and the interior members of the circle are close, and the link between circles and circles is relatively sparse. It is important to detect different community structures in social networks for wind-control information dissemination, gang fraud detection is important. For example, in the field of anti-fraud, there will be a criminal control loopholes in some platforms, which will focus on the crime, with a short time to get huge profits in a short time, showing a significant gang characteristics. In addition, community discovery concepts are also very useful in various fields of computer science, such as image segmentation and com...

AI Technical Summary

Problems solved by technology

[0005] (1) Most of the known community discovery works are general single-domain networks, but single-domain networks may contain noisy information and missing information

In addition, it is very important to analyze multi-domain networks because many hidden patterns cannot be obtained by analyzing single-domain networks

[0006] (2) A small number of community algorithms for multi-domain networks use traditional multi-layer networks (each layer network has the same number of node sets and different types of edge sets) community discovery algorithms (discover communities separately in each layer network), however , this baseline method does not consider supplementary information in multi-domain networks

Therefore, the problem of relatively high time complexity has not been well solved in the research of community discovery algorithms.

Many studies only improve the accuracy of the algorithm, but the time complexity of the algorithm is still not significantly improved

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