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» Word Sense Disambiguation by Relative Selection
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LREC
2010
153views Education» more  LREC 2010»
13 years 8 months ago
Homographic Ideogram Understanding Using Contextual Dynamic Network
Conventional methods for disambiguation problems have been using statistical methods with co-occurrence of words in their contexts. It seems that human-beings assign appropriate w...
Jun Okamoto, Shun Ishizaki
EMNLP
2009
13 years 5 months ago
Combining Collocations, Lexical and Encyclopedic Knowledge for Metonymy Resolution
This paper presents a supervised method for resolving metonymies. We enhance a commonly used feature set with features extracted based on collocation information from corpora, gen...
Vivi Nastase, Michael Strube
ACL
2003
13 years 8 months ago
Syntactic Features and Word Similarity for Supervised Metonymy Resolution
We present a supervised machine learning algorithm for metonymy resolution, which exploits the similarity between examples of conventional metonymy. We show that syntactic head-mo...
Malvina Nissim, Katja Markert
JMLR
2010
108views more  JMLR 2010»
13 years 2 months ago
Feature Selection using Multiple Streams
Feature selection for supervised learning can be greatly improved by making use of the fact that features often come in classes. For example, in gene expression data, the genes wh...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
ECML
2003
Springer
14 years 17 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 ...