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AAAI
2004
13 years 9 months ago
SenseClusters - Finding Clusters that Represent Word Senses
SenseClusters is a freely available word sense discrimination system that takes a purely unsupervised clustering approach. It uses no knowledge other than what is available in a r...
Amruta Purandare, Ted Pedersen
ICML
2010
IEEE
13 years 5 months ago
Mining Clustering Dimensions
Many real-world datasets can be clustered along multiple dimensions. For example, text documents can be clustered not only by topic, but also by the author's gender or sentim...
Sajib Dasgupta, Vincent Ng
ICCS
2005
Springer
14 years 1 months ago
Clustering Using Adaptive Self-organizing Maps (ASOM) and Applications
Abstract. This paper presents an innovative, adaptive variant of Kohonen’s selforganizing maps called ASOM, which is an unsupervised clustering method that adaptively decides on ...
Yong Wang, Chengyong Yang, Kalai Mathee, Giri Nara...
ICASSP
2010
IEEE
13 years 5 months ago
A supervisory approach to semi-supervised clustering
We propose a new approach to semi-supervised clustering that utilizes boosting to simultaneously learn both a similarity measure and a clustering of the data from given instancele...
Bryan Conroy, Yongxin Taylor Xi, Peter J. Ramadge
ICML
2004
IEEE
14 years 8 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He