Random walk social network event recommendation method based on user similarity

A random walk, similar user technology, applied in the field of electronic information, can solve the problems of no group relationship, limited number of events, sparse data, etc., to achieve the effect of improving accuracy

Pending Publication Date: 2020-07-31
上海硕恩网络科技股份有限公司
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AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a random walk social network event recommendation method based on user similarity to solve the data sparsity problem existing in the existing algorithm proposed in the above-mentioned ba

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  • Random walk social network event recommendation method based on user similarity
  • Random walk social network event recommendation method based on user similarity
  • Random walk social network event recommendation method based on user similarity

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Embodiment

[0043] see Figure 1-4 , the present invention provides a technical solution: a random walk social network event recommendation method based on user similarity, the specific method steps of the random walk social network event recommendation method based on user similarity are as follows:

[0044] S1: Event classification: According to the geographical location of the event, source website, content theme and other information, determine the feature space coordinates of the event, and further classify the event;

[0045] S2: Establishment of user similarity model: Based on the two indicators of the number of events that users participate in and the number of categories of events that they jointly participate in, the similarity between users is measured. In order to establish a model for calculating the similarity between users, the following two points are proposed Assumptions:

[0046] The more times two users participate in a single event, the higher the similarity;

[0047...

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Abstract

The invention belongs to the technical field of electronic information, and particularly relates to a random walk social network event recommendation method based on user similarity, and the method comprises the following specific steps: S1, event category division; S2, establishing a user similarity model; S3, restarting random walk of the user group network; S4, performing cold start user processing. Characteristic data of network event activities are calculated, and are fused in the group analysis of an online social network appliance; a random walk algorithm based on restart is utilized toperform community division on the users again, so the purpose of recommending events for the users, especially cold start user recommendation, is achieved, explicit and implicit feedback data in thesocial network are fully utilized, and the accuracy of a recommendation system is improved.

Description

technical field [0001] The invention relates to the field of electronic information technology, in particular to a random walk social network event recommendation method based on user similarity. Background technique [0002] The event-based social network provides a platform for users to organize events and activities. A large number of events exist on the network. The website will regularly organize certain events and activities. Users can choose their favorite events to participate in. [0003] Many scholars convert social networks into the form of graphs, and use the topological properties of graphs to complete recommendations through the analysis of nodes, edges, and weights. The basic idea is to use the random walk algorithm, and randomly walk the nodes according to certain rules. Random walks are developed on univariate Markov chains of homogeneous graphs and are widely used in the field of recommendation. [0004] In a trust-based social network, how to evaluate th...

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Application Information

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IPC IPC(8): G06F16/9535G06F17/16G06Q50/00
CPCG06F16/9535G06F17/16G06Q50/01
Inventor 黄云
Owner 上海硕恩网络科技股份有限公司
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