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» DISC: Data-Intensive Similarity Measure for Categorical Data
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SDM
2009
SIAM
217views Data Mining» more  SDM 2009»
14 years 2 months ago
A Framework for Exploring Categorical Data.
In this paper, we present a framework for categorical data analysis which allows such data sets to be explored using a rich set of techniques that are only applicable to continuou...
Shyam Boriah, Varun Chandola, Vipin Kumar
AMAI
2011
Springer
12 years 5 months ago
Similarity measures in formal concept analysis
Formal concept analysis (FCA) has been applied successively in diverse fields such as data mining, conceptual modeling, social networks, software engineering, and the semantic we...
Faris Alqadah, Raj Bhatnagar
KDD
2009
ACM
174views Data Mining» more  KDD 2009»
14 years 8 days ago
Visual exploration of categorical and mixed data sets
For categorical data there does not exist any similarity measure which is as straight forward and general as the numerical distance between numerical items. Due to this it is ofte...
Sara Johansson
ICDE
1999
IEEE
183views Database» more  ICDE 1999»
14 years 6 months ago
ROCK: A Robust Clustering Algorithm for Categorical Attributes
Clustering, in data mining, is useful to discover distribution patterns in the underlying data. Clustering algorithms usually employ a distance metric based (e.g., euclidean) simi...
Sudipto Guha, Rajeev Rastogi, Kyuseok Shim
VLDB
1998
ACM
204views Database» more  VLDB 1998»
13 years 9 months ago
Clustering Categorical Data: An Approach Based on Dynamical Systems
Wedescribea novel approachfor clustering collectionsof sets,andits applicationto theanalysis and mining of categoricaldata. By "categorical data," we meantableswith fiel...
David Gibson, Jon M. Kleinberg, Prabhakar Raghavan