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ICDM
2006
IEEE
164views Data Mining» more  ICDM 2006»
16 years 17 days ago
Unsupervised Learning of Tree Alignment Models for Information Extraction
We propose an algorithm for extracting fields from HTML search results. The output of the algorithm is a database table– a data structure that better lends itself to high-level...
Philip Zigoris, Damian Eads, Yi Zhang
ISMB
1993
15 years 7 months ago
Protein Structure Prediction: Selecting Salient Features from Large Candidate Pools
Weintroduce a parallel approach, "DT-SELECT," for selecting features used by inductive learning algorithms to predict protein secondary structure. DT-SELECTis able to ra...
Kevin J. Cherkauer, Jude W. Shavlik
DGO
2008
170views Education» more  DGO 2008»
15 years 8 months ago
Natural language processing and e-Government: crime information extraction from heterogeneous data sources
Much information that could help solve and prevent crimes is never gathered because the reporting methods available to citizens and law enforcement personnel are not optimal. Dete...
Chih Hao Ku, Alicia Iriberri, Gondy Leroy
ISBI
2011
IEEE
14 years 10 months ago
Automatic pancreas segmentation in contrast enhanced CT data using learned spatial anatomy and texture descriptors
Pancreas segmentation in 3-D computed tomography (CT) data is of high clinical relevance, but extremely difficult since the pancreas is often not visibly distinguishable from the...
Marius Erdt, Matthias Kirschner, Klaus Drechsler, ...
JASIS
2000
143views more  JASIS 2000»
15 years 6 months ago
Discovering knowledge from noisy databases using genetic programming
s In data mining, we emphasize the need for learning from huge, incomplete and imperfect data sets (Fayyad et al. 1996, Frawley et al. 1991, Piatetsky-Shapiro and Frawley, 1991). T...
Man Leung Wong, Kwong-Sak Leung, Jack C. Y. Cheng