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EMNLP
2006
13 years 9 months ago
Unsupervised Discovery of a Statistical Verb Lexicon
This paper demonstrates how unsupervised techniques can be used to learn models of deep linguistic structure. Determining the semantic roles of a verb's dependents is an impo...
Trond Grenager, Christopher D. Manning
JACM
2010
208views more  JACM 2010»
13 years 6 months ago
The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies
clustering of documents according to sharing of topics at multiple levels of abstraction. Given a corpus of documents, a posterior inference algorithm finds an approximation to a ...
David M. Blei, Thomas L. Griffiths, Michael I. Jor...
ACTAC
2006
126views more  ACTAC 2006»
13 years 7 months ago
Named Entity Recognition for Hungarian Using Various Machine Learning Algorithms
In this paper we introduce a statistical Named Entity recognizer (NER) system for the Hungarian language. We examined three methods for identifying and disambiguating proper nouns...
Richárd Farkas, György Szarvas, Andr&a...
COLT
2001
Springer
14 years 4 days ago
Agnostic Boosting
We prove strong noise-tolerance properties of a potential-based boosting algorithm, similar to MadaBoost (Domingo and Watanabe, 2000) and SmoothBoost (Servedio, 2003). Our analysi...
Shai Ben-David, Philip M. Long, Yishay Mansour
TJS
2010
182views more  TJS 2010»
13 years 6 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari