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» Hierarchically Classifying Documents Using Very Few Words
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COLING
2000
13 years 9 months ago
Word Sense Disambiguation of Adjectives Using Probabilistic Networks
In this paper, word sense dismnbiguation (WSD) accuracy achievable by a probabilistic classifier, using very milfimal training sets, is investigated. \Ve made the assuml)tiou that...
Gerald Chao, Michael G. Dyer
DAS
2004
Springer
14 years 1 months ago
A Neural Network Classifier for Junk E-Mail
Abstract. Most e-mail readers spend a non-trivial amount of time regularly deleting junk e-mail (spam) messages, even as an expanding volume of such e-mail occupies server storage ...
Ian Stuart, Sung-Hyuk Cha, Charles C. Tappert
WWW
2007
ACM
14 years 8 months ago
A new suffix tree similarity measure for document clustering
In this paper, we propose a new similarity measure to compute the pairwise similarity of text-based documents based on suffix tree document model. By applying the new suffix tree ...
Hung Chim, Xiaotie Deng
KES
2004
Springer
14 years 1 months ago
Analyzing the Temporal Sequences for Text Categorization
– This paper describes a text categorization approach that is based on a combination of a newly designed text representation with a kNN classifier. The new text document represen...
Xiao Luo, A. Nur Zincir-Heywood
CICLING
2007
Springer
14 years 2 months ago
Text Categorization for Improved Priors of Word Meaning
Distributions of the senses of words are often highly skewed. This fact is exploited by word sense disambiguation (WSD) systems which back off to the predominant (most frequent) s...
Rob Koeling, Diana McCarthy, John Carroll