Social network link recommendation method and network evolution model implementation design

A social network and recommendation algorithm technology, applied in computing, instruments, data processing applications, etc., can solve problems such as ignoring benefits and inaccurate recommendation results

Active Publication Date: 2018-06-08
BEIJING INSTITUTE OF TECHNOLOGYGY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to solve the problem that the existing recommendation algorithm only relies on the link prediction algorithm to estimate the similarity between nodes, but ignores the

Method used

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  • Social network link recommendation method and network evolution model implementation design
  • Social network link recommendation method and network evolution model implementation design
  • Social network link recommendation method and network evolution model implementation design

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Experimental program
Comparison scheme
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Embodiment 1

[0072] figure 1 The flow chart of the social network link recommendation algorithm provided by the present invention. Such as figure 1 As mentioned above, the present invention provides a link recommendation algorithm based on cost and income under limited cost. The specific steps of the algorithm are as follows:

[0073] Step a, traverse the non-neighboring nodes in the target node in the network, calculate the centrality of each node to all other reachable nodes, and the cost of establishing links; step A, specifically:

[0074] Step a.1 calculates the shortest path from each node to all other reachable nodes, thereby calculating its centrality; node centrality is determined according to formula (10):

[0075] u u (G)=∑{dist G (u,v) -1 |u≠v} (10)

[0076] Among them, dist G (u, v) represents the shortest path length from node u to node v, if node u cannot reach node v, then dist G (u, v) = ∝;

[0077] Step a.2 calculates the random walk probability from the target n...

Embodiment 2

[0112] figure 2 The flow chart of the social network evolution model provided by the present invention. Such as figure 2 As shown, the present invention provides a social network evolution model, which can explore and mine the core edge structure in the network, and the network evolution structure is consistent with the real network. details as follows:

[0113] The competition of each node in the network to choose to establish links with other nodes is non-cooperative, that is, each node in the network only pays attention to the improvement of its own centrality, and does not pay attention to the improvement of the overall centrality of the network;

[0114] Each node in the network will competitively establish links with other nodes according to the link recommendation algorithm described above;

[0115] In the process of network evolution, the cost of each round is set to the minimum cost to ensure that at least one new edge is added to the network after a round of evo...

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Abstract

The invention relates to a social network link recommendation method and network evolution model implementation design, and belongs to the technical field of network science. The invention comprises alink recommendation algorithm based on cost and income under limited price and a social network dynamic evolution design based on the game theory. The link recommendation algorithm traverses the contribution of all links for a target node by all potential links, the nodes with a highest contribution and cost ratio are selected in sequence to obtain a node set on a premise that total cost does notexceed, and then, the nodes with highest contribution are selected in sequence to realize the maximize the closeness centrality of the target node. The network evolution model implementation design assumes that the competition of nodes in the network is non-cooperation, a network evolution result is explored, and the formation of a network core-edge structure is mined. By use of the method and the design, the strong core-edge structure can be quickly evolved in a non-core-edge network.

Description

technical field [0001] The invention relates to a social network link recommendation method and a network evolution model implementation design, belonging to the field of network science and technology. Background technique [0002] As a platform for interpersonal communication, online social network is favored by more and more users with its practical and convenient mode of making friends. Using data generated by social networks for information processing, such as network evolution, influence diffusion, link prediction, etc., has also attracted a lot of attention in academia and industry. As an important research direction of social network data mining, link prediction is used to predict the probability of establishing a link between two user nodes that have no connection edges in the network. However, the use of link prediction algorithms to calculate the similarity of users in the network and recommend friends to users ignores the fact that when users choose friends, the...

Claims

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Application Information

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IPC IPC(8): G06Q50/00
CPCG06Q50/01
Inventor 郑宏蔡熠锦刘佳谋宿红毅闫波
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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