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Academic team important member identification method based on academic big data

An identification method and big data technology, applied in the field of academic network identification, to achieve the effect of low computational time complexity

Active Publication Date: 2019-04-19
DALIAN UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The present invention provides a new solution to the problem of identifying influential leader nodes and key members in an academic team

Method used

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  • Academic team important member identification method based on academic big data
  • Academic team important member identification method based on academic big data
  • Academic team important member identification method based on academic big data

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Embodiment Construction

[0044] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the specific embodiments of the present invention will be described in further detail below.

[0045] The example of the present invention provides a method for identifying important members of an academic team based on academic big data, which includes:

[0046] Step 1: Through statistical analysis of the publication of the papers in the DBLP data set and the cooperation of scholars, an academic network is constructed with the real co-authored data of the papers between scholars. The nodes in the network represent scholars, and the edges represent the cooperative relationship between scholars. Through statistical analysis of the cooperation between scholars, the method of mathematical statistics is used to analyze the cooperation behavior between scholars to find the cooperation window.

[0047] The present invention selects the paper data in the DBLP data set for experimen...

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Abstract

The invention discloses an academic team important member identification method based on academic big data, which comprises the following steps of identifying a team leader from the perspective of degree centrality, an H factor and academic age, and evaluating and marking team key members by using a DHRank model based on a PageRank method for the first time. The objective of the invention is to reasonably cluster teams. According to the method, after the leader-centered team clustering based on the shortest path is carried out, the clustering result is further improved by using a method basedon team scale comparison and leader H factor comparison, and the accuracy of the result of identifying the key members by using the DHRank model in the later period is improved. Compared with other methods, the method provided by the invention is more accurate in the aspect of finding out scholars with influence, and has lower operation time complexity. The invention provides a new method for identifying the leader and the key person in the academic team, and provides a new solution for scientific research of the team in the academic network.

Description

Technical field [0001] The invention belongs to the technical field of academic network recognition, and relates to a method for identifying important members of an academic team based on academic big data, in particular to a method for identifying multi-characteristic leader nodes with degree centrality, H factor and academic age and an improvement based on PageRank The DHRank algorithm is used to identify key members. Background technique [0002] With the diversified development of scientific research today, academic teams are developing trends that span universities, research centers, and even research fields. The extensiveness and complexity of scientific research cooperation has made the scale of academic teams increasingly larger, and the cooperative relationships between team members and teams have become more complex. Important members of the team are the backbone of a team. They not only undertake the planning and management responsibilities within the team, but also u...

Claims

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Application Information

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IPC IPC(8): G06F16/951G06F16/35
Inventor 万良田张凯源于硕
Owner DALIAN UNIV OF TECH
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