id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_g7vncqg54jbtlp6lcpqhvwtney	Zengyou He	Attribute value weighting in k-modes clustering	2011	6	.pdf	application/pdf	3846	396	70	DIVERSITY-BASED ATTRIBUTE WEIGHTING FOR K-MODES CLUSTERING information from categorical data input, it needs a clustering algorithm. Thus in this paper, we generalize a k-modes algorithm for categorical data by adding the weight and diversity value of each attribute value to optimize categorical data Keywords: categorical data, diversity, K-modes, attribute weighting. Example of simple matching approach for categorical data is k-modes [7]. matching dissimilarity clustering of data, replacing the means to modes. k-modes algorithm for clustering categorical data into account the frequency distribution of different attribute values can also be applied to the optimization of categorical data dissimilarity [1]. focuses on the k-modes clustering with diversitybased attribute weighting and the research contribution is distance values diversity to optimize the value 𝑥𝑥 in the data set D, defined as equation(1). Similarity and Dissimilarity Measure for Categorical Data in K-Modes The k-modes algorithm is widely used for clustering categorical data.	./cache/work_g7vncqg54jbtlp6lcpqhvwtney.pdf	./txt/work_g7vncqg54jbtlp6lcpqhvwtney.txt