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Social network partitioning method and system based on cloud computing

A social network and cloud computing technology, applied in the field of social network division and system based on cloud computing, can solve the problem of diagnosing whether other subjects are sick and cannot provide any help, and achieve the effect of improving the efficiency of division and utilization.

Inactive Publication Date: 2010-10-20
BEIJING UNIV OF POSTS & TELECOMM
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AI Technical Summary

Problems solved by technology

For example, to train a disease diagnosis system, its task is to diagnose whether a subject suffers from a certain infectious disease, the usual practice is to use a vector to represent a subject, and at the same time assume that the relationship between the subjects The disease conditions are independent of each other, that is, knowing a confirmed patient does not provide any help in diagnosing whether other subjects have the disease

Method used

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  • Social network partitioning method and system based on cloud computing
  • Social network partitioning method and system based on cloud computing
  • Social network partitioning method and system based on cloud computing

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Embodiment Construction

[0054] The technical scheme of the present invention can be used for data processing and community analysis, currently used for data processing and community analysis mainly based on single-machine node operation, there are the following disadvantages: 1) the amount of input data will be limited by the memory capacity; 2) applicable The program based on a single machine cannot meet the needs of more graph mining tasks, such as time performance requirements; 3) the stability is not high, and when a node has a problem, it needs to be re-run; problems are more likely to occur when running a large amount of data. The technical solution of the present invention mainly provides: a search method for extremely large cliques (wherein, a very large clique refers to a collection of points that are connected between each other in a social network) in a graph running on a single machine, and then the searched out extreme cliques are Large cliques are merged to become community divisions, an...

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Abstract

The invention provides a social network partitioning method and a system based on cloud computing, and the method comprises the steps: working out maximum groups in a social network; merging the maximum groups according to the proportion of common points among the maximum groups in corresponding maximum groups; and after merging the maximum groups and obtaining a community as a new point, connecting adjacent points by edges, thus obtaining a new social network. The social network is partitioned according to the maximum groups, the new social network is obtained by taking the merged maximum groups as the new point, and the new social network can reflect analysis needs accurately and improve the utilization ratio of the social network; and simultaneously, the maximum groups are worked out in the manner of the cloud computing, which can improve the social network partitioning efficiency.

Description

technical field [0001] The invention relates to a method and system for dividing social networks based on cloud computing. Background technique [0002] At present, the objects processed by data mining tasks are mainly individual data instances, which can often be represented by a vector containing multiple attribute values, and these data instances are assumed to be statistically independent. For example, to train a disease diagnosis system, its task is to diagnose whether a subject suffers from a certain infectious disease, the usual practice is to use a vector to represent a subject, and at the same time assume that the relationship between the subjects The disease conditions are independent of each other, that is, knowing a confirmed patient does not provide any help in diagnosing whether other subjects have the disease. Intuitive experience tells us that this assumption is unreasonable. If a person's relatives and friends suffer from the infectious disease, he is more ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 吴斌杨娟王柏杨胜琦李凯平周春燕
Owner BEIJING UNIV OF POSTS & TELECOMM
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