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A Distributed User Clustering Method for Social Networks

A social network and user clustering technology, applied in the field of distributed user clustering, can solve problems such as difficult to meet needs, achieve the effect of improving efficiency and reducing computing overhead

Active Publication Date: 2022-07-29
INST OF SOFTWARE - CHINESE ACAD OF SCI
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The traditional social network-oriented user clustering method is based on a single-machine serial algorithm, which is obviously difficult to meet the existing needs.

Method used

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  • A Distributed User Clustering Method for Social Networks
  • A Distributed User Clustering Method for Social Networks
  • A Distributed User Clustering Method for Social Networks

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Embodiment Construction

[0033] The present invention will be described in detail below with reference to specific embodiments and accompanying drawings.

[0034] The social network-oriented distributed user clustering method proposed by the present invention is applied in the Spark big data processing system.

[0035] Based on the above information, the specific implementation steps of this embodiment are as follows.

[0036] 1. Through the message passing mechanism, each node exposes its unique Id to its neighbors, that is, each node can save the neighbor's Id information.

[0037] 2. The edge fusion strategy is used to calculate the node similarity, and the calculation is concentrated on the edge rather than each node. Through the neighbor information obtained in step 1, for any adjacent nodes v and w, the nodes have their own neighbor sets, which are Γ(v) and Γ(w) respectively. On the edge e where the two are connected, the relative second-order node similarity between v and w is calculated as σ...

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Abstract

The invention discloses a social network-oriented distributed user clustering method, the steps of which include: 1) generating a user relationship graph according to social network graph data; 2) dividing the user relationship graph based on a node segmentation method, and Distribute to different machines; 3) Calculate the similarity between the two nodes according to the neighbor node list of the two nodes connected to the edge; 4) Determine the attribute value of the edge according to whether the similarity on the edge is greater than the set threshold e and send it to the two nodes connected to the edge. Each node adds the received attribute values ​​to obtain the attribute value of the node. If the attribute value of the node is greater than the threshold μ, the node is regarded as the core node; 5) Each The machine where the core node is located sends the label of its own node to adjacent nodes to update the node's own label; when no core node modifies its own label, the nodes with the same label are divided into a cluster.

Description

technical field [0001] The invention relates to a distributed user clustering method oriented to a social network, and belongs to the technical field of software. Background technique [0002] A social network is a network structure composed of many nodes and relationships between nodes. A node usually refers to an individual or organization (also known as a community). Social networks represent the kinds of social relationships through which people or organizations are connected, from casual acquaintances to close family ties. The process of dividing a collection of physical or abstract objects into classes of similar objects is called clustering. A cluster generated by clustering is a collection of data objects that are similar to objects in the same cluster and different from objects in other clusters. User clustering in social networks is to divide closely connected user nodes into a cluster, and user nodes in the same cluster are closely connected, while user nodes i...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V10/762G06K9/62G06Q50/00
CPCG06Q50/01G06F18/23
Inventor 黄涛许利杰王伟郑莹莹章凯
Owner INST OF SOFTWARE - CHINESE ACAD OF SCI
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