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EMNLP
2004
13 years 9 months ago
Unsupervised WSD based on Automatically Retrieved Examples: The Importance of Bias
This paper explores the large-scale acquisition of sense-tagged examples for Word Sense Disambiguation (WSD). We have applied the "WordNet monosemous relatives" method t...
Eneko Agirre, David Martínez
GECCO
2007
Springer
195views Optimization» more  GECCO 2007»
14 years 2 months ago
MILCS: a mutual information learning classifier system
This paper introduces a new variety of learning classifier system (LCS), called MILCS, which utilizes mutual information as fitness feedback. Unlike most LCSs, MILCS is specifical...
Robert Elliott Smith, Max Kun Jiang
FORTE
2004
13 years 9 months ago
Symbolic Diagnosis of Partially Observable Concurrent Systems
Abstract. Monitoring large distributed concurrent systems is a challenging task. In this paper we formulate (model-based) diagnosis by means of hidden state history reconstruction,...
Thomas Chatain, Claude Jard
IDEAL
2004
Springer
14 years 1 months ago
In-Situ Learning in Multi-net Systems
Abstract. Multiple classifier systems based on neural networks can give improved generalisation performance as compared with single classifier systems. We examine collaboration in ...
Matthew C. Casey, Khurshid Ahmad
CICLING
2009
Springer
14 years 8 months ago
Semi-supervised Clustering for Word Instances and Its Effect on Word Sense Disambiguation
We propose a supervised word sense disambiguation (WSD) system that uses features obtained from clustering results of word instances. Our approach is novel in that we employ semi-s...
Kazunari Sugiyama, Manabu Okumura