R. JIN ET AL.
Copyright © 2013 SciRes. ENG
classify the rest of the herbs. The results showed that 2 53
herbal medicines were reasonably classified as 14 types
such as sort of invigoration, clearing heat, diuresis, treat-
ing impediment disease and treating gynecological dis-
ease, while the other 112 medicines were classified into
112 individual types. The same high similarity to differ-
ent known types might be the main reason for those ind i-
vidual herbs. Table 5 showed the major clusters involv-
ing more than 10 herbs.
4. Conclusion
Data mining is a promising technology which can be
applied in analyzing vast amounts of TCM data for in-
vestigating novel knowledge. In this paper, we provided
a kind of multidimensional table that was suited for the
data in ancient Chinese materia medica books, in order to
assist resear chers to manage the data in an efficient way.
Moreover, we also introduced two illustrative studies of
mining meaningful patterns in the three-dimensional ta-
ble of SCMM. The results provided evidence that the
multidimensional table could facilitate data mining
works in TCM.
Table 5. Representative clusters.
Type
Clusters
Total
number Examples Efficacy
1 105 Radi x ginseng
Radix Glycyrrhizae Invigoration
2 50 Radix Scutellaria
Fructus Gardenia Clearing heat
3 30 Rhizoma Ligustici Wallichi
Radix Angelicae Sinensis T
disease
4 15 Rhizoma Podophyllum
Scolopendra Subspinipes T
caused by ghost
5 12 Nidus Vespae
Calculus Bovis Treating fright
palpitation
6 11 Folium Pyrrosiae
Semen Plantaginis Diuresis
7 10 Radix Aconiti Carmichaeli
Fructus Evodiae Treating impediment
disease
5. Acknowledgements
This work is supported by China 973 project (2007-
CB512605), the Scientific Research Innovation Team of
Beijing University of Chinese Medicine (2011-CXTD-14)
and Hui-Chun Chin and Tsung-Dao Lee Chinese Under-
graduate Research Endowment (second author).
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