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» Mining Local Data Sources For Learning Global Cluster Models
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SAC
2009
ACM
14 years 2 months ago
Combining statistics and semantics via ensemble model for document clustering
Incorporating background knowledge into data mining algorithms is an important but challenging problem. Current approaches in semi-supervised learning require explicit knowledge p...
Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan
ICDM
2003
IEEE
104views Data Mining» more  ICDM 2003»
14 years 28 days ago
Localized Prediction of Continuous Target Variables Using Hierarchical Clustering
In this paper, we propose a novel technique for the efficient prediction of multiple continuous target variables from high-dimensional and heterogeneous data sets using a hierarch...
Aleksandar Lazarevic, Ramdev Kanapady, Chandrika K...
FLAIRS
2007
13 years 10 months ago
Mining Sequences in Distributed Sensors Data for Energy Production
The desire to predict power generation at a given point in time is essential to power scheduling, energy trading, and availability modeling. The research conducted within is conce...
Mehmed M. Kantardzic, John Gant
SDM
2008
SIAM
176views Data Mining» more  SDM 2008»
13 years 9 months ago
A General Model for Multiple View Unsupervised Learning
Multiple view data, which have multiple representations from different feature spaces or graph spaces, arise in various data mining applications such as information retrieval, bio...
Bo Long, Philip S. Yu, Zhongfei (Mark) Zhang
SETN
2004
Springer
14 years 1 months ago
Incremental Mixture Learning for Clustering Discrete Data
Abstract. This paper elaborates on an efficient approach for clustering discrete data by incrementally building multinomial mixture models through likelihood maximization using the...
Konstantinos Blekas, Aristidis Likas