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ICDM
2002
IEEE
143views Data Mining» more  ICDM 2002»
15 years 11 months ago
A Hybrid Approach to Discover Bayesian Networks From Databases Using Evolutionary Programming
This paper describes a novel data mining approach that employs evolutionary programming to discover knowledge represented in Bayesian networks. There are two different approaches ...
Man Leung Wong, Shing Yan Lee, Kwong-Sak Leung
ICIC
2009
Springer
15 years 11 months ago
Dimension Reduction Using Semi-Supervised Locally Linear Embedding for Plant Leaf Classification
Plant has plenty use in foodstuff, medicine and industry, and is also vitally important for environmental protection. So, it is important and urgent to recognize and classify plant...
Shanwen Zhang, Kwok-Wing Chau
CIKM
2011
Springer
14 years 6 months ago
Emerging topic detection using dictionary learning
Streaming user-generated content in the form of blogs, microblogs, forums, and multimedia sharing sites, provides a rich source of data from which invaluable information and insig...
Shiva Prasad Kasiviswanathan, Prem Melville, Arind...
AAAI
2007
15 years 8 months ago
Discovering Multivariate Motifs using Subsequence Density Estimation and Greedy Mixture Learning
The problem of locating motifs in real-valued, multivariate time series data involves the discovery of sets of recurring patterns embedded in the time series. Each set is composed...
David Minnen, Charles Lee Isbell Jr., Irfan A. Ess...
BMCBI
2005
89views more  BMCBI 2005»
15 years 6 months ago
An empirical analysis of training protocols for probabilistic gene finders
Background: Generalized hidden Markov models (GHMMs) appear to be approaching acceptance as a de facto standard for state-of-the-art ab initio gene finding, as evidenced by the re...
William H. Majoros, Steven Salzberg