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ICDM
2006
IEEE
108views Data Mining» more  ICDM 2006»
15 years 3 months ago
Spatial Multidimensional Sequence Clustering
Measurements at different time points and positions in large temporal or spatial databases requires effective and efficient data mining techniques. For several parallel measureme...
Ira Assent, Ralph Krieger, Boris Glavic, Thomas Se...
KDD
2002
ACM
138views Data Mining» more  KDD 2002»
15 years 10 months ago
Learning to match and cluster large high-dimensional data sets for data integration
Part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. In integrating databases found on the Web or obtained by us...
William W. Cohen, Jacob Richman
GECCO
2007
Springer
308views Optimization» more  GECCO 2007»
15 years 3 months ago
Multiobjective clustering with automatic k-determination for large-scale data
Web mining - data mining for web data - is a key factor of web technologies. Especially, web behavior mining has attracted a great deal of attention recently. Behavior mining invo...
Nobukazu Matake, Tomoyuki Hiroyasu, Mitsunori Miki...
KDD
2009
ACM
182views Data Mining» more  KDD 2009»
15 years 10 months ago
Scalable graph clustering using stochastic flows: applications to community discovery
Algorithms based on simulating stochastic flows are a simple and natural solution for the problem of clustering graphs, but their widespread use has been hampered by their lack of...
Venu Satuluri, Srinivasan Parthasarathy
KDD
2012
ACM
235views Data Mining» more  KDD 2012»
13 years 2 days ago
A near-linear time approximation algorithm for angle-based outlier detection in high-dimensional data
Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...
Ninh Pham, Rasmus Pagh