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PAKDD
2007
ACM
184views Data Mining» more  PAKDD 2007»
15 years 5 months ago
A Fast Algorithm for Finding Correlation Clusters in Noise Data
Abstract. Noise significantly affects cluster quality. Conventional clustering methods hardly detect clusters in a data set containing a large amount of noise. Projected clusterin...
Jiuyong Li, Xiaodi Huang, Clinton Selke, Jianming ...
CVPR
2011
IEEE
14 years 3 months ago
Max-margin Clustering: Detecting Margins from Projections of Points on Lines
Given a unlabelled set of points X ∈ RN belonging to k groups, we propose a method to identify cluster assignments that provides maximum separating margin among the clusters. We...
Raghuraman Gopalan, Jagan Sankaranarayanan
SOCIALCOM
2010
14 years 9 months ago
Measuring Similarity between Sets of Overlapping Clusters
The typical task of unsupervised learning is to organize data, for example into clusters, typically disjoint clusters (eg. the K-means algorithm). One would expect (for example) a...
Mark K. Goldberg, Mykola Hayvanovych, Malik Magdon...
JDCTA
2010
464views more  JDCTA 2010»
14 years 6 months ago
A New Agglomerative Hierarchical Clustering Algorithm Implementation based on the Map Reduce Framework
Text clustering is one of the difficult and hot research fields in the text mining research. Combing Map Reduce framework and the neuron initialization method of VPSOM (vector pre...
Hui Gao, Jun Jiang, Li She, Yan Fu
DMKD
1997
ACM
308views Data Mining» more  DMKD 1997»
15 years 3 months ago
A Fast Clustering Algorithm to Cluster Very Large Categorical Data Sets in Data Mining
Partitioning a large set of objects into homogeneous clusters is a fundamental operation in data mining. The k-means algorithm is best suited for implementing this operation becau...
Zhexue Huang