A Competency Mining Method Based on Latent Dirichlet Allocation (LDA) Model

A text mining approach based on latent Dirichlet allocation (LDA) is proposed to analyze the competency characteristics. First, we briefly introduce the principle and hypothesis of latent Dirichlet allocation (LDA) model. Second, we elaborate the idea of using LDA topic model to extract competency,...

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Bibliographic Details
Published in:Journal of physics. Conference series 2020-11, Vol.1682 (1), p.12059
Main Authors: Wu, Jiying, Son, Guandong, Wang, Sihui
Format: Article
Language:English
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Summary:A text mining approach based on latent Dirichlet allocation (LDA) is proposed to analyze the competency characteristics. First, we briefly introduce the principle and hypothesis of latent Dirichlet allocation (LDA) model. Second, we elaborate the idea of using LDA topic model to extract competency, Then, we use Chinese text materials such as biographies and interviews of Chinese scientific and technological talents as data sources to conduct experiments, and obtain four competency topics including knowledge, attitude, quality and values. The research results preliminarily verify the effectiveness of latent Dirichlet allocation (LDA) model in competency research, but there are still many details to be improved in the future.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1682/1/012059