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» Supervised Term Weighting for Automated Text Categorization
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SAC
2006
ACM
14 years 1 months ago
Exploiting partial decision trees for feature subset selection in e-mail categorization
In this paper we propose PARTfs which adopts a supervised machine learning algorithm, namely partial decision trees, as a method for feature subset selection. In particular, it is...
Helmut Berger, Dieter Merkl, Michael Dittenbach
DGO
2008
126views Education» more  DGO 2008»
13 years 9 months ago
Active learning for e-rulemaking: public comment categorization
We address the e-rulemaking problem of reducing the manual labor required to analyze public comment sets. In current and previous work, for example, text categorization techniques...
Stephen Purpura, Claire Cardie, Jesse Simons
ERCIMDL
2006
Springer
204views Education» more  ERCIMDL 2006»
13 years 11 months ago
Comparing and Combining Two Approaches to Automated Subject Classification of Text
A machine-learning and a string-matching approach to automated subject classification of text were compared, as to their performance, advantages and downsides. The former approach ...
Koraljka Golub, Anders Ardö, Dunja Mladenic, ...
DOCENG
2006
ACM
14 years 1 months ago
NEWPAR: an automatic feature selection and weighting schema for category ranking
Category ranking provides a way to classify plain text documents into a pre-determined set of categories. This work proposes to have a look at typical document collections and ana...
Fernando Ruiz-Rico, José Luis Vicedo Gonz&a...
ICML
2003
IEEE
14 years 8 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty