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» Using Decision Trees to Construct a Practical Parser
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LREC
2010
180views Education» more  LREC 2010»
13 years 9 months ago
Parsing to Stanford Dependencies: Trade-offs between Speed and Accuracy
We investigate a number of approaches to generating Stanford Dependencies, a widely used semantically-oriented dependency representation. We examine algorithms specifically design...
Daniel Cer, Marie-Catherine de Marneffe, Daniel Ju...
ECAI
2004
Springer
14 years 28 days ago
Tractable Symmetry Breaking Using Restricted Search Trees
We present a new conceptual abstraction in symmetry breaking – the GE-tree. The construction and traversal of a GE-tree breaks all symmetries in any constraint satisfaction or si...
Colva M. Roney-Dougal, Ian P. Gent, Tom Kelsey, St...
KDD
1998
ACM
120views Data Mining» more  KDD 1998»
13 years 11 months ago
Large Datasets Lead to Overly Complex Models: An Explanation and a Solution
This paper explores unexpected results that lie at the intersection of two common themes in the KDD community: large datasets and the goal of building compact models. Experiments ...
Tim Oates, David Jensen
NLP
2000
13 years 11 months ago
Learning Rules for Large-Vocabulary Word Sense Disambiguation: A Comparison of Various Classifiers
In this article we compare the performance of various machine learning algorithms on the task of constructing word-sense disambiguation rules from data. The distinguishing characte...
Georgios Paliouras, Vangelis Karkaletsis, Ion Andr...
IJCAI
2003
13 years 9 months ago
Inductive Learning in Less Than One Sequential Data Scan
Most recent research of scalable inductive learning on very large dataset, decision tree construction in particular, focuses on eliminating memory constraints and reducing the num...
Wei Fan, Haixun Wang, Philip S. Yu, Shaw-hwa Lo