Browse > Article
http://dx.doi.org/10.6116/kjh.2015.30.3.63.

HF-IFF: Applying TF-IDF to Measure Symptom-Medicinal Herb Relevancy and Visualize Medicinal Herb Characteristics - Studying Formulations in Cheongkangeuigam -  

Oh, Junho (Korea Institute of Oriental Medicine)
Publication Information
The Korea Journal of Herbology / v.30, no.3, 2015 , pp. 63-68 More about this Journal
Abstract
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 ： 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 ： 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 ： 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.
Keywords
Medicine; East Asian Traditional; Data Mining; TF-IDF; HF-IFF; Herbal Formula;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
1 Lee JH, Kim WY, Oh JH. Study on quantization of Korean medicine terminology concept - for disease symptom terms of Compilation of Formulas and Medicinals Addendum -. J Korean Med Class. 2014 ; 27(1) : 99–109.   DOI   ScienceOn
2 Peng W. Dictionary of Chinese medicine prescription. 1st ed. Beijing : People's Medical Publishing House. 2005 : 3-4.
3 Baek JU, Lee BW. Extended indications of Four - Constitution Medicinal formula analyzing composition on Dongeuibogam formula Ⅱ. J Korean Med Hist. 2013 ; 26(2) : 23–9.
4 Lee BW, Baek JU. Extended indications of Four - Constitution Medicinal formula analyzing composition on Dongeuibogam formula - The case of Bojungyikgi - tang for So - Eum type -. J Korean Med Class. 2013 ; 26(3) : 99–109.   DOI   ScienceOn
5 Wu YH, Kim KW, Lee BW, Kim EH. Analysis of Prescriptions from Taepyeonghyeminhwajegukbang, Somunsunmyungronbang and Nansilbijang. J Korean Med Class. 2014 ; 27(4) : 121–31.   DOI   ScienceOn
6 Kim KW, Kim TY, Lee BW. Prescriptions from Taepyeonghyeminhwajegukbang, Somunsunmyungronbang and Nansilbijang based on Herb weight ratio grade. J Korean Med Class. 2014 ; 27(4) : 73–84.   DOI   ScienceOn
7 Yang DH. Data mining analysis on relationship between disease pattern and materia medica in Bangyakhappyeon. Seoul : Kyunghee Univ. 2011 : 1-77.
8 Aizawa A. An information-theoretic perspective of tf–idf measures. Inf Process Manag. 2003 ; 39(1) : 45–65.   DOI   ScienceOn
9 Wu HC, Luk RWP, Wong KF, Kwok KL. Interpreting TF-IDF Term Weights As Making Relevance Decisions. ACM Trans Inf Syst. 2008 ; 26(3) : 13:1–13:37.   DOI   ScienceOn
10 Jure Leskovec, Anand Rajaraman, Jeffrey D. Ullman. Mining of Massive Datasets. Mining of Massive Datasets. New York : Cambridge University Press. 2011 : 7–9.
11 Oh JH. A Study on the Organization and Contents of "CheongKangEuiGam". J Korean Med Hist. 2014 ; 27(2) : 63–74.
12 Oh JH. HF-IFF demo page. Retrieved Mar 14 2015, from http://pinedance.github.io/demo.html#/HF-IFF