Network node semantic information mining method and device, storage medium and electronic equipment

A technology for semantic information and network nodes, applied in semantic analysis, digital data processing, natural language data processing, etc., can solve problems such as low efficiency and inaccurate mining results, and avoid low efficiency and network node semantic information mining results. Objective and accurate results
CN113971406APending Publication Date: 2022-01-25HEFEI UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN ยท China
Current Assignee / Owner
HEFEI UNIV OF TECH
Publication Date
2022-01-25

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Abstract

The invention provides a network node semantic information mining method and device, a storage medium and electronic equipment, and relates to the technical field of network node semantic information mining. According to the technical scheme, the weighted undirected network between the enterprises is constructed based on the enterprise text data, and the negative event mapping function is constructed by using the rule-based event mining algorithm and the time decay function, so that the enterprise negative event information is mined, and mining node semantic information of the weighted undirected network by using an improved PageRank algorithm and negative event information. According to the method, the influence of human subjectivity on a network node semantic information mining process is avoided, manual operation is replaced by a computer and a corresponding algorithm, the problems of low efficiency and high cost during data processing are avoided, and a network node semantic information mining result is more objective, accurate, real and effective.
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Description

technical field

[0001] The invention relates to the technical field of network node semantic information mining, in particular to a network node semantic information mining method, device, storage medium and electronic equipment. Background technique

[0002] The influence of network nodes generally refers to the influence of nodes on other nodes by virtue of the association relationship between nodes. However, this association is a structural relationship and does not contain the semantic information implied by the nodes themselves. Therefore, only mining the structural influence of network nodes cannot fully reflect the influence of network nodes, that is, the complete semantic information of network nodes cannot be obtained. For example, the greater the influence of an enterprise (which can be regarded as a node) in the enterprise network, the more resources or risks the enterprise spreads to other enterprises. Resources or risks are two different semantic information. ...

Claims

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