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» Evaluating learning algorithms and classifiers
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KDD
2004
ACM
163views Data Mining» more  KDD 2004»
14 years 9 months ago
Exploiting dictionaries in named entity extraction: combining semi-Markov extraction processes and data integration methods
We consider the problem of improving named entity recognition (NER) systems by using external dictionaries--more specifically, the problem of extending state-of-the-art NER system...
William W. Cohen, Sunita Sarawagi
GIS
2009
ACM
14 years 24 days ago
Classification of raster maps for automatic feature extraction
Raster maps are widely available and contain useful geographic features such as labels and road lines. To extract the geographic features, most research work relies on a manual st...
Yao-Yi Chiang, Craig A. Knoblock
BMCBI
2005
100views more  BMCBI 2005»
13 years 8 months ago
Speeding disease gene discovery by sequence based candidate prioritization
Background: Regions of interest identified through genetic linkage studies regularly exceed 30 centimorgans in size and can contain hundreds of genes. Traditionally this number is...
Euan A. Adie, Richard R. Adams, Kathryn L. Evans, ...
HUC
2010
Springer
13 years 9 months ago
Bayesian recognition of motion related activities with inertial sensors
This work presents the design and evaluation of an activity recognition system for seven important motion related activities. The only sensor used is an Inertial Measurement Unit ...
Korbinian Frank, Maria Josefa Vera Nadales, Patric...
ICML
2010
IEEE
13 years 10 months ago
Large Scale Max-Margin Multi-Label Classification with Priors
We propose a max-margin formulation for the multi-label classification problem where the goal is to tag a data point with a set of pre-specified labels. Given a set of L labels, a...
Bharath Hariharan, Lihi Zelnik-Manor, S. V. N. Vis...