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» Learning Classifiers from Semantically Heterogeneous Data
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CIKM
2008
Springer
13 years 9 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan
IRES
2002
63views more  IRES 2002»
13 years 7 months ago
The Semantic Web, universalist ambition and some lessons from librarianship
Building the semantic web encounters problems similar to building large bibliographic systems. The experience of librarianship in controlling large, heterogeneous collections of b...
Terrence A. Brooks
KDD
2010
ACM
272views Data Mining» more  KDD 2010»
13 years 11 months ago
Beyond heuristics: learning to classify vulnerabilities and predict exploits
The security demands on modern system administration are enormous and getting worse. Chief among these demands, administrators must monitor the continual ongoing disclosure of sof...
Mehran Bozorgi, Lawrence K. Saul, Stefan Savage, G...
IUI
2005
ACM
14 years 1 months ago
Intelligent data entry assistant for XML using ensemble learning
XML has emerged as the primary standard of data representation and data exchange [13]. Although many software tools exist to assist the XML implementation process, data must be ma...
Danico Lee, Costas Tsatsoulis
COLING
2008
13 years 9 months ago
The Effect of Syntactic Representation on Semantic Role Labeling
Almost all automatic semantic role labeling (SRL) systems rely on a preliminary parsing step that derives a syntactic structure from the sentence being analyzed. This makes the ch...
Richard Johansson, Pierre Nugues