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논문 기본정보

HF-IFF: TF-IDF를 응용한 병증-본초 연관성(relevancy) 측정과 본초 특성의 시각화 -청강의감 방제를 대상으로-

논문 개요

기관명, 저널명, ISSN, ISBN 으로 구성된 논문 개요 표입니다.
기관명 NDSL
저널명 大韓本草學會誌 = The Korea journal of herbology
ISSN 1229-1765,
ISBN

논문저자 및 소속기관 정보

저자, 소속기관, 출판인, 간행물 번호, 발행연도, 초록, 원문UR, 첨부파일 순으로 구성된 논문저자 및 소속기관 정보표입니다
저자(한글)
저자(영문)
소속기관
소속기관(영문)
출판인
간행물 번호
발행연도 2015-01-01
초록 Objectives : We applied the term weighting method used in the field of data search to quantify relevancy between symptoms and medicinal herbs, and, based on this, we aim to introduce a method of visualizing the characteristics of medicinal herbs. Methods #65306; We proposed HF-IFF, an adaptation of TF-IDF, which is a term weighting measurement method adapted in the field of data search. Using this method, we deduced relevancy between symptoms and medicinal herbs In Cheongkangeuigam that was published in 1984 by organizing the medical theory of Cheongkang, Kim Younghoon, and visualized this as a graph in order to compare the characteristics of medicinal herbs used for different symptoms. Results #65306; HF-IFF is the product of HF and IFF, where HF is the frequency of the relevant medicinal herb for a set of symptoms, and IFF is the inverse of the number of formulations (FF) containing that herb. A total of 251 types of medicinal herb are used in Cheongkangeuigam, and 1538 formulations are classified according to 67 types of symptom. The overall mean for HF-IFF was 0.491, with a maximum of 4.566 and a minimum of 0.013. Conclusions #65306; In spite of several limitations, we were able to use HF-IFF to measure relevancy between symptoms and medicinal herbs, with formulations as an intermediate. We were able to use the quantified results to visually express the characteristics of the herbs used for symptoms by bubble chart and word-cloud from HF-IFF.
원문URL http://click.ndsl.kr/servlet/OpenAPIDetailView?keyValue=03553784&target=NART&cn=JAKO201525966510141
첨부파일

추가정보

과학기술표준분류, ICT 기술분류,DDC 분류,주제어 (키워드) 순으로 구성된 추가정보표입니다
과학기술표준분류
ICT 기술분류
DDC 분류
주제어 (키워드) Medicine,East Asian Traditional,Data Mining,TF-IDF,HF-IFF,Herbal Formula