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» Learning Probabilistic Models of Word Sense Disambiguation
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SAC
2005
ACM
15 years 3 months ago
A hierarchical naive Bayes mixture model for name disambiguation in author citations
Because of name variations, an author may have multiple names and multiple authors may share the same name. Such name ambiguity affects the performance of document retrieval, web ...
Hui Han, Wei Xu, Hongyuan Zha, C. Lee Giles
CIKM
2011
Springer
13 years 9 months ago
Focusing on novelty: a crawling strategy to build diverse language models
Word prediction performed by language models has an important role in many tasks as e.g. word sense disambiguation, speech recognition, hand-writing recognition, query spelling an...
Luciano Barbosa, Srinivas Bangalore
NAACL
2010
14 years 7 months ago
Probabilistic Frame-Semantic Parsing
This paper contributes a formalization of frame-semantic parsing as a structure prediction problem and describes an implemented parser that transforms an English sentence into a f...
Dipanjan Das, Nathan Schneider, Desai Chen, Noah A...
ACL
2003
14 years 11 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
15 years 5 days 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