Academic core author excavation and related information extraction method and system based on complex network

Abstract

The invention belongs to the field of data mining, aims to solve the problem of excavating core authors in an academic field and intelligently extracting related information of the authors, and provides an improved academic core author excavation and information extraction method and system based on a core node discovery algorithm in the social network analysis technology. The method combines the vertical search technology, the social network analysis technology and the text analysis technology, and can find the core authors or groups of the academic field in the mass of information to further obtain related information of the authors. The method uses the vertical search technology to collect open source literature data, uses the bibliometric technology and the complex network analysis technology to analyze the importance of a variety of social entities in the data, and utilizes a community discovery algorithm to perform entity clustering based on the closeness degree of relationships between entities to find out an academic community. Users can find the core authors or an institution according to an entity importance ranking, and find the leadership team according to published articles amount distribution of cooperative groups.

Description

technical field [0001] The invention relates to the field of data mining, in particular to a complex network-based academic core author mining and related information extraction method and system. Background technique [0002] Many practical networks have a common property, that is, they are all connected by various communities through public nodes. The connections between nodes within a community are relatively tight, and the connections between communities are relatively sparse. For example, the World Wide Web can be seen as being composed of a large number of website communities, and many sites within the same community often discuss some topics of common interest. Similarly, in the author cooperation network or circuit network, each node can also be divided into different communities according to its different properties. Therefore, the number of communities in the network and the belonging community and number of each node are of great significance to the study of com...

AI Technical Summary

Problems solved by technology

[0007] The present invention aims at the problem of digging core figures in a certain academic field and intelligently extracting their relevant information. The present invention proposes an improved academic core author mining and information extraction algorithm and system based on the core node discovery method in social network analysis technology

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