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A Distributed PageRank Acceleration Method Based on Similarity Estimation

A similarity and distributed technology, applied in the field of computer networks, can solve problems such as unguaranteed, slow convergence speed, large amount of calculation, etc., and achieve the effect of reducing the number of encounters, speeding up the speed, and accelerating the convergence speed

Active Publication Date: 2021-11-09
ZHENGZHOU SEANET TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The purpose of the present invention is to provide a distributed PageRank acceleration method based on similarity estimation in order to overcome the problems of slow convergence speed and large amount of calculation in distributed PageRank
However, if the nodes are only randomly selected, there is no guarantee that the selected nodes can provide the maximum amount of information, resulting in slow convergence

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  • A Distributed PageRank Acceleration Method Based on Similarity Estimation
  • A Distributed PageRank Acceleration Method Based on Similarity Estimation
  • A Distributed PageRank Acceleration Method Based on Similarity Estimation

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Embodiment Construction

[0062] A distributed PageRank acceleration method based on similarity estimation according to the present invention will be described in detail below with reference to the drawings and embodiments.

[0063] Such as figure 1 As shown, the present invention proposes a distributed PageRank acceleration method based on similarity estimation, and its steps are as follows:

[0064] Step 1) Each subgraph calculates the feature vector representing its own successor metaset information:

[0065] The subgraph model is represented by a directed graph G, G=(V,E). V={v 1 ,v 2 ,...,v n} is the vertex set, E={e 1 ,e 2 ,...,e m} is an edge set. The number of nodes is n=|V|, and the number of edges is m=|E|. v i ∈V, (i=1,2,…,n), represents a node of the subgraph. (v i ,v j ) ∈ E, representing the node v i to node v j a directed edge of

[0066] Compute the successor set S of subgraphs. The successor metaset S is defined as:

[0067] S={u|u∈V∧(v,u)∈E∧u≠v}

[0068] According t...

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Abstract

The present invention provides a distributed PageRank acceleration method based on similarity estimation, said method comprising: step 1) taking each node in the network as a central node, constructing a subgraph of the connection relationship between the central node and the adjacent nodes of the network ;Each subgraph calculates the eigenvector representing its own successor metaset information; step 2) the current subgraph calculates the similarity between the successor metaset of the encountered object and its own vertex set, and decides whether to add the ID of the encountered object to itself according to the preset threshold the candidate list; step 3) the current subgraph adds the subgraph in the candidate list of the encounter object to its own candidate list, and the encounter object adds the subgraph in the candidate list of the current subgraph to its own candidate list; step 4) calculates the vertices of the current subgraph The similarity between the set and the successor meta-sets of all candidate objects, the one with the highest similarity is taken as the object of the next formal encounter; step 5) According to the interaction between the two sub-graphs at the time of encounter, calculate and update all the PageRank value.

Description

technical field [0001] The invention relates to the technical field of computer networks, in particular to a distributed PageRank acceleration method based on similarity estimation. Background technique [0002] The total resources of user terminal equipment in the network are huge, such as computing and storage resources owned by smart phones, set-top boxes, routers, PCs and other devices, but these resources are still idle and have not been rationally utilized. However, the total amount of resources deployed by service providers is limited, and service bottlenecks will continue to appear. We hope that through the local information around the network nodes, we can accurately and quickly find the terminal devices with strong service capabilities, great influence, and real proximity to users to deploy content resources. The existing methods of approximating local information to global information have a slow convergence speed. Therefore, we hope to accelerate the convergenc...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/953
CPCG06F16/951
Inventor 尤佳莉张欣薛寒星刘学
Owner ZHENGZHOU SEANET TECH CO LTD
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