Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (6A): 680-685.doi: 10.11896/jsjkx.210800123

• Interdiscipline & Application • Previous Articles     Next Articles

Complex Network Analysis on Curriculum System of Data Science and Big Data Technology

YANG Bo, LI Yuan-biao   

  1. Data Science Research Center,Kunming University of Science and Technology,Kunming 650500,China
    Faculty of Science,Kunming University of Science and Technology,Kunming 650500,China
  • Online:2022-06-10 Published:2022-06-08
  • About author:YANG Bo,born in 1987,Ph.D.His main research interests include statistical physics and complex systems,complex network,text data mining and visualization.
  • Supported by:
    National Natural Science Foundation of China(11947041).

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Abstract: In recent years,more and more universities have begun to offer majors in data science and big data technology.As an emerging and popular multi-disciplinary major with wide caliber,its curriculum system is still being furthered improved.In this paper,we use complex network methods to analyze and visualize the course data set of 106 universities collected from the Internet.The course co-occurrence network and college relationship network are constructed respectively.For the highly coupled course co-occurrence network,a shell decomposition algorithm based on edge weights is proposed.The results are compared with the word frequency statistics and the frequent items obtained by the Apriori algorithm.Considering that this speciality can award a degree in science or engineering,the data set is divided into two sections science and engineering to analyze and visualize.This research can provide a certain reference to universities which are establishing or have established data science and big data technology speciality,and also provide an effective algorithm for the analysis of highly coupled networks.

Key words: Complex network, Course co-occurrence network, Frequent items, Shell decomposition algorithm

CLC Number: 

  • TP391
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