Social network node influence recommendation system based on local nodes and degree discounts
A network node, social network technology, applied in the field of social network node influence recommendation system, can solve problems such as affecting user purchase rate
Active Publication Date: 2020-12-29
杭州麻瓜网络科技有限公司
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Problems solved by technology
The modeling of social networks can also be applied to the field of viral marketing, where the influence of nodes can be measured by the number of nodes that can be activated to adopt new technologies or purchase new products. For example, if a company wants to promote products, it hopes to use viral First select a small number of people to try the product to be promoted for free, and when the selected users are satisfied with the product, they will recommend the product to their colleagues and friends through online social networks, so that more people can understand And finally buy the product; how to find out these people to try the product and make the number of people who buy the product the most is the core issue that needs to be considered, that is, to maximize the impact of the product on the user purchase rate
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[0100] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.
[0101] 1 Introduction
[0102] 1.1 Background
[0103] The influence maximization problem was first proposed by Domingos and Richardson et al., and then Kempe and Kleinberg et al. further proposed that given a social network graph, a specific influence cascade model and a small k, find k in the graph vertices, the expected number of vertices influenced by k seeds is the maximum possible under the influence cascade model. Kempe et al. proved that the optimization problem is NP-hard and gave a greedy approximation algorithm for these thr...
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The invention provides a social network node influence recommendation system based on local nodes and degree discounts. The social network node influence recommendation system comprises a network nodeacquisition module, a calculation screening module and a diffusion recommendation module, the data output end of the network node acquisition module is connected with the data output end of the calculation screening module, and the data output end of the calculation screening module is connected with the data input end of the diffusion recommendation module; the network node acquisition module isused for acquiring a to-be-recommended node set; the calculation screening module is used for calculating a local influence value in the node set acquired by the network node acquisition module; screening out the node with the maximum local influence value as a source node; forming a candidate node set by the screened source nodes; and the diffusion recommendation module is used for carrying outnode diffusion on candidate nodes in the candidate node set by utilizing the global influence value, and diffusion nodes are recommended nodes. Product recommendation can be performed on the nodes.
Description
technical field [0001] The invention relates to the technical field of social network, in particular to a social network node influence recommendation system based on local nodes and degree discounts. Background technique [0002] In the era of Web2.0, online social network has attracted more and more attention from people. It connects people and things and things together. While generating a large amount of data, it also spreads information widely. While online social networks are gradually being used by more people, they are also widely used in more fields. Moreover, with the transformation of the Internet model, the information interaction between people has gradually shifted from offline to online, making it easier to contact and track traditional social relationships. The problem of maximizing influence is brought out under such a background. It aims to select seed nodes among numerous nodes as seed nodes for information dissemination, so as to maximize the influence o...
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IPC IPC(8): G06F16/9535G06F16/9536G06Q50/00
CPCG06Q50/01G06F16/9535G06F16/9536
Inventor 刘小洋吴松阳李祥
Owner 杭州麻瓜网络科技有限公司