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» Learning Expressive Models for Word Sense Disambiguation
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ECML
2003
Springer
14 years 27 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 ...
ICASSP
2011
IEEE
12 years 11 months ago
Toward text message normalization: Modeling abbreviation generation
This paper describes a text normalization system for deletion-based abbreviations in informal text. We propose using statistical classifiers to learn the probability of deleting ...
Deana Pennell, Yang Liu
ISMIR
2004
Springer
190views Music» more  ISMIR 2004»
14 years 1 months ago
Disambiguating Music Emotion Using Software Agents
Annotating music poses a cognitive load on listeners and this potentially interferes with the emotions being reported. One solution is to let software agents learn to make the ann...
Dan Yang, WonSook Lee
NIPS
2000
13 years 9 months ago
A Neural Probabilistic Language Model
A goal of statistical language modeling is to learn the joint probability function of sequences of words in a language. This is intrinsically difficult because of the curse of dim...
Yoshua Bengio, Réjean Ducharme, Pascal Vinc...
AIED
2009
Springer
14 years 2 months ago
Assessing Student Paraphrases Using Lexical Semantics and Word Weighting
We present in this paper an approach to assessing student paraphrases in the intelligent tutoring system iSTART. The approach is based on measuring the semantic similarity between ...
Vasile Rus, Mihai C. Lintean, Arthur C. Graesser, ...