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» Feature selection methods for text classification
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AAAI
2004
15 years 3 days ago
Bayesian Network Classifiers Versus k-NN Classifier Using Sequential Feature Selection
The aim of this paper is to compare Bayesian network classifiers to the k-NN classifier based on a subset of features. This subset is established by means of sequential feature se...
Franz Pernkopf
DOCENG
2006
ACM
15 years 4 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...
KDD
2009
ACM
269views Data Mining» more  KDD 2009»
15 years 11 months ago
Extracting discriminative concepts for domain adaptation in text mining
One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from different underlying distributi...
Bo Chen, Wai Lam, Ivor Tsang, Tak-Lam Wong
NLDB
2004
Springer
15 years 4 months ago
Acquiring Selectional Preferences from Untagged Text for Prepositional Phrase Attachment Disambiguation
Abstract. Extracting information automatically from texts for database representation requires previously well-grouped phrases so that entities can be separated adequately. This pr...
Hiram Calvo, Alexander F. Gelbukh
KDD
2007
ACM
139views Data Mining» more  KDD 2007»
15 years 11 months ago
Raising the baseline for high-precision text classifiers
Many important application areas of text classifiers demand high precision and it is common to compare prospective solutions to the performance of Naive Bayes. This baseline is us...
Aleksander Kolcz, Wen-tau Yih