Artikel,
Applying Clustering and Association Rule Learning for Finding Patterns in Herbal Formulae
ACEEE International Journal on Network Security, 3 (2): 3 (April 2012)
Zusammenfassung
Traditional herbal formulae can be usually
characterized by the use of several herbs. Various patterns of
combinations from these herbs can be applied on a disease. In
this paper, we apply two techniques of data mining, i.e.,
clustering and association rule learning, for finding patterns
of herbal formulae with main category of muscle pain and
fatigue and several subcategories. With clustering technique,
it facilitates herbal experts to find the set of clusters with
appropriated subcategories. The association rule learning is
applied on the all formulae and formulae on each cluster of
the selected set to find the important patterns of combinations.
The results show that data mining techniques are useful for
finding patterns in herbal formulae.
