一种基于重叠社区标签传播的学科划分方法

doi:10.13998/j.cnki.issn1002-1248.20-0307

Abstract

Abstract: [Purpose/Significance] Online encyclopedias such as Wikipedia include a large number of concepts. However, in such encyclopedias, there are no clear divisions between concepts and concepts, between concepts and disciplines, and between disciplines and disciplines. It embarrasses junior researchers regarding a certain discipline to obtain domain relevant knowledge in a systematic and low-efficiency manner. [Method/Process] To obtain information in a specific subject area and organize knowledge better, a new algorithm is designed for subject division. Specifically, approaches in complex network analysis are introduced for subject division, which helps to build a topic text network by the classical topic model. Then, the overlapping community label propagation algorithm is improved to identify the boundaries of different subject divisions. [Results/Conclusions] Finally, 300 Wikipedia entry texts were investigated as samples to evaluate the effectiveness of the proposed algorithm. Categories of experiments were conducted to analyze the community structure of the entry network and the complexity of the subject division, which helps to provide a corpus to build a subject knowledge base.

Key words: subject division, complex network, overlapping community, topic model

CLC Number:

G302

TI Huiying, GENG Qian, JIN Jian. A COPRA Based Algorithm for Subject Division[J].Journal of Library and Information Science in Agriculture, 2021, 33(1): 41-52.

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