A robust and scalable clustering algorithm for mixed type attributes in large database environment

By Tom Chiu, DongPing Fang, John Chen, Yao Wang, Christopher Jeris. Knowledge Discovery and Data Mining, 2001

795 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/a1ddee7a0c4885b46891d5d8f873e9388d42a4c1

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Citations in the corpus

Reference Group Influences among Chinese Travelers (2006, methodology): “…(1) preclustering the cases (or records) into many small subclusters by constructing a cluster features (CF) tree, and (2) clustering the subclusters resulting from the first stage into a desired number of clusters— a probabilistic hierarchical cluster analysis (Chiu et al. 2001; SPSS 2003).”
Job types and job quality in Europe (2013, methodology): “Advantages of twostep cluster analysis over other cluster analysis methods are that it can include categorical and continuous variables and be used with very large data sets (Chiu et al., 2001; Norusis, 2003).”
Exploring the Attitudes-Action Gap in Household Resource Consumption: Does “Environmental Lifestyle” Segmentation Align with Consumer Behaviour? (2013, positive): “This approach [47,48] allows an automatic choice for the number of clusters based on changes in the Bayes Information Criterion.”
Open innovation modes and the role of internal R&D (2011, methodology): “The analysis was done with standardized variables and with Log-Likelihood as a distance measure ( Chiu et al. , 1999”
Determining the number of clusters/segments in hierarchical clustering/segmentation algorithms (2004, methodology): “The next section describes evaluation graphs, followed by a description of the L method.”
Capital Structure Decisions During a Firm's Life Cycle (2011, methodology): “The two-step cluster analysis employed here is an exploratory tool designed to reveal natural groupings (or clusters) within a dataset that would otherwise not be apparent (Chiu et al. 2001; He et al. 2005).”
Ecogeographical land characterization maps as a tool for assessing plant adaptation and their implications in agrobiodiversity studies (2012, methodology): “Keywords Abiotic adaptation Bonferroni confidence intervals Geographic information systems Germplasm characterization Map evaluation Two-step clustering”
A Survey of Clustering Data Mining Techniques (2006, result): “This approach is shared by other similar systems [Chiu et al. 2001].”
SPSS TwoStep Cluster - a first evaluation (2004, methodology): “Chiu et al. (2001) report excellent results for the proposed algorithm to determine the number of clusters automatically.”