most citedAn Optimization Model for Outlier Detection in Categorical Data

58 citations · 207 across the 11 of their papers we have counts for

collaborators

11 papers

cs.AI200531 cited

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…

cs.AI200552 cited

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…

cs.DB200515 cited

A Fast Greedy Algorithm for Outlier Mining

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. In [38], the problem of outlier detection i…

cs.DB20053 cited

A Unified Subspace Outlier Ensemble Framework for Outlier Detection in High Dimensional Spaces

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…

cs.DB200558 cited

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…

cs.DB20052 cited

Mining Top-k Approximate Frequent Patterns

Zengyou He

Frequent pattern (itemset) mining in transactional databases is one of the most well-studied problems in data mining. One obstacle that limits the practical usage of frequent patte…