Extracting method of overlay network

A technology of superimposing network and extraction methods, applied in network data retrieval, network data indexing, other database retrieval and other directions, can solve problems such as low efficiency, and achieve the effect of improving efficiency and small network scale

Inactive Publication Date: 2017-06-30
HANGZHOU DIANZI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Obviously this search algorithm requires access to v bi , v bj All nodes and possible paths between, less efficient

Method used

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  • Extracting method of overlay network
  • Extracting method of overlay network
  • Extracting method of overlay network

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Experimental program
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Embodiment Construction

[0054] specific implementation

[0055] The present invention will be further described below in conjunction with drawings and embodiments.

[0056] An extraction method applicable to overlay networks, the specific steps are as follows:

[0057] Step (1), representation and index of network nodes;

[0058] The network node refers to the intersection point of two edges in the network, or a position point with specific attributes on the edge.

[0059] For a network G=(V,E), it is represented by an adjacency list, and the adjacency list represents an array Adj containing |V| lists, where each list corresponds to a node in V. For each node u∈V, the adjacency list Adj[u] contains all nodes v satisfying the condition (u, v)∈E, that is, Adj[u] contains all nodes adjacent to node u. Nodes in the adjacency list can be stored in any order. figure 1 is an adjacency list representation of a network.

[0060] Use Vb to represent some kind of network node set with special properties, if ...

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Abstract

The invention relates to an extracting method of an overlay network. The overlay network composed of nodes with the same attributes in one network is extracted. The method comprises the steps that an adjacency list is adopted to represent all nodes in a network, by distinguishing the nodes with the different attributes, the adjacent nodes with the same attribute are firstly searched for, and after the adjacency relation of all the similar nodes is obtained, an adjacency matrix is used for representing the overlay network with the same attribute. The matrix comprises the shortest path between any two adjacent nodes with the same attribute. According to the extracting method of the overlay network, one network, the marked nodes with the special attributes in the network and weights of all edges are input, and the overlay network composed of the nodes with the special attributes is output, and the network only contains the nodes with the special attributes, and has a small network scale, and thus the efficiency of calculating the shortest patch among the nodes with the special attributes in subsequent searching is improved.

Description

technical field [0001] The invention belongs to the technical field of computer applications, and relates to a method for extracting superimposed networks, which is especially suitable for hierarchical data processing of large-scale networks, such as bus station networks in road networks, extraction of a specific attribute network in online social networks, etc. . Background technique [0002] In applications such as geographic information systems and social networks, road networks or social relationship networks are important basic information structures. With the development of technology, people often face the problem of processing massive network node and edge data. In a practical application, it is often necessary to solve a specific problem, and the strategy of searching all nodes and edges in a network will bring efficiency problems. Therefore, for a specific problem, extracting a specific network to speed up the problem solving is of great significance for improvin...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/29G06F16/951G06F16/9537
Inventor 曹冠杰徐建
Owner HANGZHOU DIANZI UNIV
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