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» An Empirical Study on Class-Based Word Sense Disambiguation
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WWW
2011
ACM
13 years 2 months ago
A word at a time: computing word relatedness using temporal semantic analysis
Computing the degree of semantic relatedness of words is a key functionality of many language applications such as search, clustering, and disambiguation. Previous approaches to c...
Kira Radinsky, Eugene Agichtein, Evgeniy Gabrilovi...
ACL
2010
13 years 5 months ago
Improving the Use of Pseudo-Words for Evaluating Selectional Preferences
This paper improves the use of pseudowords as an evaluation framework for selectional preferences. While pseudowords originally evaluated word sense disambiguation, they are now c...
Nathanael Chambers, Daniel Jurafsky
ECML
2003
Springer
14 years 25 days ago
Combined Optimization of Feature Selection and Algorithm Parameters in Machine Learning of Language
Comparative machine learning experiments have become an important methodology in empirical approaches to natural language processing (i) to investigate which machine learning algor...
Walter Daelemans, Véronique Hoste, Fien De ...
NLPRS
2001
Springer
14 years 1 days ago
Ensembling based on Feature Space Restructuring with Application to WSD
We propose a new ensembling method of Support Vector Machines (SVMs) based on Feature Space Restructuring. In the proposed method, the weighted majority voting method is applied f...
Hiroya Takamura, Hiroyasu Yamada, Taku Kudo, Kaoru...
SAC
2009
ACM
14 years 2 months ago
Combining statistics and semantics via ensemble model for document clustering
Incorporating background knowledge into data mining algorithms is an important but challenging problem. Current approaches in semi-supervised learning require explicit knowledge p...
Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan