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» Landscape of Clustering Algorithms
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ALT
2009
Springer
16 years 3 months ago
Agnostic Clustering
Motivated by the principle of agnostic learning, we present an extension of the model introduced by Balcan, Blum, and Gupta [3] on computing low-error clusterings. The extended mod...
Maria-Florina Balcan, Heiko Röglin, Shang-Hua...
ACL
2008
15 years 8 months ago
Inducing Gazetteers for Named Entity Recognition by Large-Scale Clustering of Dependency Relations
We propose using large-scale clustering of dependency relations between verbs and multiword nouns (MNs) to construct a gazetteer for named entity recognition (NER). Since dependen...
Jun'ichi Kazama, Kentaro Torisawa
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
16 years 7 months ago
Density-based clustering for real-time stream data
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
Yixin Chen, Li Tu
ICDM
2008
IEEE
193views Data Mining» more  ICDM 2008»
16 years 1 months ago
Multiplicative Mixture Models for Overlapping Clustering
The problem of overlapping clustering, where a point is allowed to belong to multiple clusters, is becoming increasingly important in a variety of applications. In this paper, we ...
Qiang Fu, Arindam Banerjee
FQAS
2004
Springer
126views Database» more  FQAS 2004»
16 years 3 hour ago
Cluster Characterization through a Representativity Measure
Clustering is an unsupervised learning task which provides a decomposition of a dataset into subgroups that summarize the initial base and give information about its structure. We ...
Marie-Jeanne Lesot, Bernadette Bouchon-Meunier