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EMMCVPR
2003
Springer
15 years 3 months ago
Watershed-Based Unsupervised Clustering
In this paper, a novel general purpose clustering algorithm is presented, based on the watershed algorithm. The proposed approach defines a density function on a suitable lattice,...
Manuele Bicego, Marco Cristani, Andrea Fusiello, V...
TJS
2010
182views more  TJS 2010»
14 years 8 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari
114
Voted
SDM
2009
SIAM
220views Data Mining» more  SDM 2009»
15 years 7 months ago
Bayesian Cluster Ensembles.
Cluster ensembles provide a framework for combining multiple base clusterings of a dataset to generate a stable and robust consensus clustering. There are important variants of th...
Hongjun Wang, Hanhuai Shan, Arindam Banerjee
74
Voted
SIGIR
1998
ACM
15 years 2 months ago
Web Document Clustering: A Feasibility Demonstration
Users of Web search engines are often forced to sift through the long ordered list of document “snippets” returned by the engines. The IR community has explored document cluste...
Oren Zamir, Oren Etzioni
APWEB
2009
Springer
14 years 8 months ago
Core-Tag Clustering for Web 2.0 Based on Multi-similarity Measurements
Along with the development of Web2.0, folksonomy has become a hot topic related to data mining, information retrieval and social network. The tag semantic is the key for deep under...
Yexi Jiang, Changjie Tang, Kaikuo Xu, Lei Duan, Li...