id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_vckd3ttwbjgldfrgzguiw7srf4	Chung-Chian Hsu	Incremental clustering of mixed data based on distance hierarchy	2008	9	.pdf	application/pdf	6706	816	70	resonance theory network (M-ART) and the conceptual hierarchy tree to solve similar degrees of mixed data. algorithm can process the mixed data and has a great effect on clustering. Keywords: Adaptive resonance theory network; Conceptual hierarchy; Clustering algorithm; Unsupervised neural network; Data mining A common practice to clustering mixed dataset is to transform categorical values into numeric values and then proceed to use a numeric clustering algorithm. Hsu & Wang, 2005) to propose a new incremental clustering algorithm for mixed datasets, in which the similarity Traditional clustering algorithm transfers Favorite_Drink categorical attributes into a binary numerical Traditional clustering algorithm transfers Favorite_Drink categorical attributes into binary numerical attribute type. Entropy values for Student dataset with clusters by ART2, K-prototype The categorical attribute prototype for Adult dataset with 1–8 clusters by M-ART Incremental clustering of mixed data based on distance hierarchy Incremental clustering of mixed data based on distance hierarchy Clustering hybrid data based on distance hierarchy Clustering hybrid data based on distance hierarchy	./cache/work_vckd3ttwbjgldfrgzguiw7srf4.pdf	./txt/work_vckd3ttwbjgldfrgzguiw7srf4.txt