Thematic analysis of China's medical insurance policy based on LDA model
Pages 133 - 137
Abstract
This paper utilizes the LDA theme model, Word2Vec model, and co-occurrence analysis to identify themes in China's health insurance policy, and interprets and discusses the theme identification results. Relevant textual data on China's health insurance policies were collected and organized, and textual computational methods such as LDA, Word2Vec and co-occurrence analysis were comprehensively used to extract themes, extract key themes in the policy texts, interpret and analyze the extracted themes, and explore the characteristics of each theme. Through the determination of the optimal theme model, four themes were finally obtained and summarized, namely administrative law enforcement, remote rescue, drug trading, and network supervision. Based on the research and trend analysis of the four themes, it can be concluded that the future medical insurance policy will continue to improve and perfect in terms of equity, service quality, payment method and information construction.
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Published In
August 2024
443 pages
ISBN:9798400710353
DOI:10.1145/3697467
Copyright © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.
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Association for Computing Machinery
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Published: 08 November 2024
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IoTML 2024
IoTML 2024: 2024 4th International Conference on Internet of Things and Machine Learning
August 9 - 11, 2024
Nanchang, China
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