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» Evaluating learning algorithms and classifiers
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ML
2000
ACM
124views Machine Learning» more  ML 2000»
15 years 4 months ago
Text Classification from Labeled and Unlabeled Documents using EM
This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents. ...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
EACL
2006
ACL Anthology
15 years 5 months ago
Example-Based Metonymy Recognition for Proper Nouns
Metonymy recognition is generally approached with complex algorithms that rely heavily on the manual annotation of training and test data. This paper will relieve this complexity ...
Yves Peirsman
EMNLP
2006
15 years 5 months ago
Learning Information Status of Discourse Entities
In this paper we address the issue of automatically assigning information status to discourse entities. Using an annotated corpus of conversational English and exploiting morpho-s...
Malvina Nissim
KDD
2005
ACM
99views Data Mining» more  KDD 2005»
16 years 4 months ago
Determining an author's native language by mining a text for errors
In this paper, we show that stylistic text features can be exploited to determine an anonymous author's native language with high accuracy. Specifically, we first use automat...
Moshe Koppel, Jonathan Schler, Kfir Zigdon
MLDM
2005
Springer
15 years 10 months ago
Clustering Large Dynamic Datasets Using Exemplar Points
In this paper we present a method to cluster large datasets that change over time using incremental learning techniques. The approach is based on the dynamic representation of clus...
William Sia, Mihai M. Lazarescu