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» On Learning Decision Trees with Large Output Domains
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EMNLP
2007
13 years 9 months ago
A Comparative Evaluation of Deep and Shallow Approaches to the Automatic Detection of Common Grammatical Errors
This paper compares a deep and a shallow processing approach to the problem of classifying a sentence as grammatically wellformed or ill-formed. The deep processing approach uses ...
Joachim Wagner, Jennifer Foster, Josef van Genabit...
DAWAK
2006
Springer
13 years 11 months ago
Learning Classifiers from Distributed, Ontology-Extended Data Sources
Abstract. There is an urgent need for sound approaches to integrative and collaborative analysis of large, autonomous (and hence, inevitably semantically heterogeneous) data source...
Doina Caragea, Jun Zhang 0002, Jyotishman Pathak, ...
ISCI
2007
130views more  ISCI 2007»
13 years 7 months ago
Learning to classify e-mail
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a sup...
Irena Koprinska, Josiah Poon, James Clark, Jason C...
ML
2000
ACM
154views Machine Learning» more  ML 2000»
13 years 7 months ago
Lazy Learning of Bayesian Rules
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...
Zijian Zheng, Geoffrey I. Webb
ACL
2006
13 years 9 months ago
Morphological Richness Offsets Resource Demand - Experiences in Constructing a POS Tagger for Hindi
In this paper we report our work on building a POS tagger for a morphologically rich language- Hindi. The theme of the research is to vindicate the stand that- if morphology is st...
Smriti Singh, Kuhoo Gupta, Manish Shrivastava, Pus...