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» Learning Expressive Models for Word Sense Disambiguation
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ACL
2003
13 years 9 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
FLAIRS
2008
13 years 10 months ago
A Semantic Method for Textual Entailment
The problem of recognizing textual entailment (RTE) has been recently addressed using syntactic and lexical models with some success. Here, we further explore this problem, this t...
Andrew Neel, Max H. Garzon, Vasile Rus
SIGIR
2004
ACM
14 years 1 months ago
An effective approach to document retrieval via utilizing WordNet and recognizing phrases
Noun phrases in queries are identified and classified into four types: proper names, dictionary phrases, simple phrases and complex phrases. A document has a phrase if all content...
Shuang Liu, Fang Liu, Clement T. Yu, Weiyi Meng
WWW
2008
ACM
14 years 8 months ago
Which "Apple" are you talking about ?
In a higher level task such as clustering of web results or word sense disambiguation, knowledge of all possible distinct concepts in which an ambiguous word can be expressed woul...
Mandar Rahurkar, Dan Roth, Thomas S. Huang
CCIA
2007
Springer
14 years 1 months ago
Semantic disambiguation of taxonomies
Polysemy is one of the most difficult problems when dealing with natural language resources. Consequently, automated ontology learning from textual sources (such as web resources) ...
David Sánchez, Antonio Moreno