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SIGIR
2008
ACM
15 years 2 months ago
Semi-supervised spam filtering: does it work?
The results of the 2006 ECML/PKDD Discovery Challenge suggest that semi-supervised learning methods work well for spam filtering when the source of available labeled examples diff...
Mona Mojdeh, Gordon V. Cormack
JCP
2007
143views more  JCP 2007»
15 years 2 months ago
Noisy K Best-Paths for Approximate Dynamic Programming with Application to Portfolio Optimization
Abstract— We describe a general method to transform a non-Markovian sequential decision problem into a supervised learning problem using a K-bestpaths algorithm. We consider an a...
Nicolas Chapados, Yoshua Bengio
109
Voted
JUCS
2007
74views more  JUCS 2007»
15 years 2 months ago
A WebQuest Framework to Improve the Study of Deadlock and Process Synchronization
: The impact of the Internet on Society also affects learning at University. Students use not only printed books and their own notes, but also the information available on the Net...
Luis Panizo, Ramón-Ángel Ferná...
134
Voted
CORR
2004
Springer
125views Education» more  CORR 2004»
15 years 2 months ago
Word Sense Disambiguation by Web Mining for Word Co-occurrence Probabilities
This paper describes the National Research Council (NRC) Word Sense Disambiguation (WSD) system, as applied to the English Lexical Sample (ELS) task in Senseval-3. The NRC system ...
Peter D. Turney
134
Voted
COLING
2002
15 years 2 months ago
A Maximum Entropy-based Word Sense Disambiguation System
In this paper, a supervised learning system of word sense disambiguation is presented. It is based on conditional maximum entropy models. This system acquires the linguistic knowl...
Armando Suárez, Manuel Palomar