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» Hybrid Learning Scheme for Data Mining Applications
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ML
2006
ACM
13 years 7 months ago
XRules: An effective algorithm for structural classification of XML data
Abstract XML documents have recently become ubiquitous because of their varied applicability in a number of applications. Classification is an important problem in the data mining ...
Mohammed Javeed Zaki, Charu C. Aggarwal
KDD
2008
ACM
159views Data Mining» more  KDD 2008»
14 years 8 months ago
Semi-supervised learning with data calibration for long-term time series forecasting
Many time series prediction methods have focused on single step or short term prediction problems due to the inherent difficulty in controlling the propagation of errors from one ...
Haibin Cheng, Pang-Ning Tan
SDM
2011
SIAM
256views Data Mining» more  SDM 2011»
12 years 10 months ago
Temporal Structure Learning for Clustering Massive Data Streams in Real-Time
This paper describes one of the first attempts to model the temporal structure of massive data streams in real-time using data stream clustering. Recently, many data stream clust...
Michael Hahsler, Margaret H. Dunham
CORR
2010
Springer
173views Education» more  CORR 2010»
13 years 8 months ago
CONCISE: Compressed 'n' Composable Integer Set
Bit arrays, or bitmaps, are used to significantly speed up set operations in several areas, such as data warehousing, information retrieval, and data mining, to cite a few. Howeve...
Alessandro Colantonio, Roberto Di Pietro
ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
14 years 2 months ago
Sparse Least-Squares Methods in the Parallel Machine Learning (PML) Framework
—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...
Ramesh Natarajan, Vikas Sindhwani, Shirish Tatikon...