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AI
2002
Springer
13 years 8 months ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
SDM
2012
SIAM
261views Data Mining» more  SDM 2012»
11 years 11 months ago
Combining Active Learning and Dynamic Dimensionality Reduction
To date, many active learning techniques have been developed for acquiring labels when training data is limited. However, an important aspect of the problem has often been neglect...
Mustafa Bilgic
DATAMINE
2007
135views more  DATAMINE 2007»
13 years 8 months ago
Experiencing SAX: a novel symbolic representation of time series
Many high level representations of time series have been proposed for data mining, including Fourier transforms, wavelets, eigenwaves, piecewise polynomial models etc. Many researc...
Jessica Lin, Eamonn J. Keogh, Li Wei, Stefano Lona...
ASUNAM
2009
IEEE
14 years 3 months ago
Modeling a Store's Product Space as a Social Network
A market basket is a set of products that form a single retail transaction. This purchase data of products can shed important light on how product(s) might influence sales of oth...
Troy Raeder, Nitesh V. Chawla
KDD
2003
ACM
157views Data Mining» more  KDD 2003»
14 years 9 months ago
Cross-training: learning probabilistic mappings between topics
Classification is a well-established operation in text mining. Given a set of labels A and a set DA of training documents tagged with these labels, a classifier learns to assign l...
Sunita Sarawagi, Soumen Chakrabarti, Shantanu Godb...