Network Information Propagation Method Based on Length Constraint and Non-repeated Path

Abstract

A network information dissemination method based on length constraints and non-repeating paths, which mainly solves the problem of user trust dissemination in social networks. The steps of the present invention are: 1. Establish a trust network graph model; 2. Determine the intermediate network node; 3. Select the optimal path; 4. Calculate the information value of the network node; 5. Spread network information; 6. Discard untrustworthy network information . The invention effectively maintains the structural attributes of the trust network and improves the usability of the trust network by establishing a trust network graph model and selecting an optimal path. The present invention uses the total number of non-repeated paths from the initial node to the terminal node of the optimal path to calculate the network information acceptance degree from the initial node to the terminal node, and effectively improves the integrity of the trust network while ensuring the integrity of the trust network. Accuracy of network information between nodes.

Description

technical field [0001] The invention belongs to the technical field of computers, and further relates to a network information dissemination method based on length constraints and non-repetitive paths in the technical field of data mining. The invention can be used in complex networks such as microblog, social networking and e-commerce to disseminate trust information such as text and evaluation among different nodes. Background technique [0002] Networks such as social networking and e-commerce are typical complex networks. In this complex network, each person or individual is abstracted as a network node, and the relationship between people is abstracted as the connection between corresponding nodes in the network. The degree of association between nodes can be abstracted as the weight of corresponding edges in the network, thus forming a complex network model, and the trust information of adjacent nodes in the network can be expressed by the weights between nodes. The i...

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that because this method introduces additional impact factors, which increases the uncertainty of the relationship between nodes, it cannot accurately describe the trust relationship between nodes.

The disadvantage of this method is that because this method randomly deletes local network edges in the social network platform, it destroys the topology of the network to a large extent, resulting in the problem of low usability of the deleted network.

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