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ECAI
2000
Springer
13 years 11 months ago
Naive Bayes and Exemplar-based Approaches to Word Sense Disambiguation Revisited
Abstract. This paper describes an experimental comparison between two standard supervised learning methods, namely Naive Bayes and Exemplar–basedclassification, on the Word Sens...
Gerard Escudero, Lluís Màrquez, Germ...
COLING
1996
13 years 8 months ago
Role of Word Sense Disambiguation in Lexical Acquisition: Predicting Semantics from Syntactic Cues
This paper addresses the issue of word-sense ambiguity in extraction from machine-readable resources for the construction of large-scale knowledge sources. We describe two experim...
Bonnie J. Dorr, Douglas A. Jones
JMLR
2012
11 years 9 months ago
Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing
Open-text semantic parsers are designed to interpret any statement in natural language by inferring a corresponding meaning representation (MR – a formal representation of its s...
Antoine Bordes, Xavier Glorot, Jason Weston, Yoshu...
SIGIR
2005
ACM
14 years 28 days ago
Noun sense induction using web search results
This paper presents an algorithm for unsupervised noun sense induction, based on clustering of Web search results. The algorithm does not utilize labeled training instances or any...
Goldee Udani, Shachi Dave, Anthony Davis, Tim Sibl...
SMC
2007
IEEE
14 years 1 months ago
Sense based organization of descriptive data
— In this paper we propose a new technique allowing to map descriptive data into relative distance space, which is based primarily on senses of the terms stored in our data. We u...
M. Shahriar Hossain, Monika Akbar, Rafal A. Angryk