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We extracted major topic by applying natural language processing and keyword extracting using TF, TF-IDF, TextRank, Yake, KeyBERT. 1452 consultation data were collected from the website and official hospital e-mail.… Click to show full abstract
We extracted major topic by applying natural language processing and keyword extracting using TF, TF-IDF, TextRank, Yake, KeyBERT. 1452 consultation data were collected from the website and official hospital e-mail. We found six topics categorized into "Medical opinion" related to hospital characteristics and "Non-medical service guidance". Based on this result, it is necessary to establish marketing plan and develop a digital solution for effective consultation.
Keywords:
language processing;
modeling international;
topic modeling;
natural language
Journal Title: Studies in health technology and informatics
Year Published: 2022
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Journal Title: Studies in health technology and informatics
Year Published: 2022
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!