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ACL
2003
15 years 3 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
TNN
1998
125views more  TNN 1998»
15 years 1 months ago
Symbolic connectionism in natural language disambiguation
Abstract—Natural language understanding involves the simultaneous consideration of a large number of different sources of information. Traditional methods employed in language an...
Samuel W. K. Chan, James Franklin
TKDE
2010
182views more  TKDE 2010»
15 years 8 days ago
MILD: Multiple-Instance Learning via Disambiguation
In multiple-instance learning (MIL), an individual example is called an instance and a bag contains a single or multiple instances. The class labels available in the training set ...
Wu-Jun Li, Dit-Yan Yeung
TSD
2005
Springer
15 years 7 months ago
Modelling Lexical Stress
Human listeners use lexical stress for word segmentation and disambiguation. We look into using lexical stress for speech recognition by examining a Dutch-language corpus. We propo...
Rogier C. van Dalen, Pascal Wiggers, Léon J...
EMNLP
2010
14 years 12 months ago
A New Approach to Lexical Disambiguation of Arabic Text
We describe a model for the lexical analysis of Arabic text, using the lists of alternatives supplied by a broad-coverage morphological analyzer, SAMA, which include stable lemma ...
Rushin Shah, Paramveer S. Dhillon, Mark Liberman, ...