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» Sampling Methods for Unsupervised Learning
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134
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CCIA
2007
Springer
15 years 8 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
112
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AGENTS
2000
Springer
15 years 7 months ago
BoB: an interactive improvisational music companion
This paper introduces a new domain for believable agents (BA) and presents novel methods for dealing with the unique challenges that arise therein. The domain is providing improvi...
Belinda Thom
126
Voted
ICA
2007
Springer
15 years 6 months ago
Phase-Aware Non-negative Spectrogram Factorization
Non-negative spectrogram factorization has been proposed for single-channel source separation tasks. These methods operate on the magnitude or power spectrogram of the input mixtur...
R. Mitchell Parry, Irfan A. Essa
121
Voted
GECCO
2006
Springer
144views Optimization» more  GECCO 2006»
15 years 6 months ago
On semi-supervised clustering via multiobjective optimization
Semi-supervised classification uses aspects of both unsupervised and supervised learning to improve upon the performance of traditional classification methods. Semi-supervised clu...
Julia Handl, Joshua D. Knowles
115
Voted
EMNLP
2007
15 years 4 months ago
Building Lexicon for Sentiment Analysis from Massive Collection of HTML Documents
Recognizing polarity requires a list of polar words and phrases. For the purpose of building such lexicon automatically, a lot of studies have investigated (semi-) unsupervised me...
Nobuhiro Kaji, Masaru Kitsuregawa