58 citations · 157 across the 7 of their papers we have counts for
7 papers
K-Histograms: An Efficient Clustering Algorithm for Categorical Dataset
Zengyou He, Xiaofei Xu, Shengchun Deng +1
Clustering categorical data is an integral part of data mining and has attracted much attention recently. In this paper, we present k-histogram, a new efficient algorithm for clust…
Clustering Mixed Numeric and Categorical Data: A Cluster Ensemble Approach
Zengyou He, Xiaofei Xu, Shengchun Deng
Clustering is a widely used technique in data mining applications for discovering patterns in underlying data. Most traditional clustering algorithms are limited to handling datase…
An Optimization Model for Outlier Detection in Categorical Data
Zengyou He, Xiaofei Xu, Shengchun Deng
The task of outlier detection is to find small groups of data objects that are exceptional when compared with rest large amount of data. Detection of such outliers is important for…
Clustering Categorical Data Streams
Zengyou He, Xiaofei Xu, Shengchun Deng +1
The data stream model has been defined for new classes of applications involving massive data being generated at a fast pace. Web click stream analysis and detection of network int…
A Link Clustering Based Approach for Clustering Categorical Data
Zengyou He, Xiaofei Xu, Shengchun Deng
Categorical data clustering (CDC) and link clustering (LC) have been considered as separate research and application areas. The main focus of this paper is to investigate the commo…
Modeling Complex Higher Order Patterns
Zengyou He, Xiaofei Xu, Shengchun Deng
The goal of this paper is to show that generalizing the notion of frequent patterns can be useful in extending association analysis to more complex higher order patterns. To that e…