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Text Categorization Methods Using Topical Importance Characteristic used the Twenty Newsgroups dataset. The result of classifiers' performance on different subsets shows
TOPIC CLUSTERIZATION OF NEWS ARTICLESThe Twenty Newsgroups
Feature Selection for Text Classification of a News Flows based on Topical Importance Characteristic and Multinomial Naïve Bayes. The Accuracy of classification results was tested in the “20-Newsgroups” dataset
"The Vegetarian Twenties" in Zakhar Prilepin’s the Monastery"The Vegetarian Twenties" in Zakhar Prilepin’s the Monastery
Study of the Method of Classification of News Based on Distributive Semantics of classification is shown. As a set of data was taken “The 20 Newsgroups dataset”. Presented results of a
Improving unsupervised neural aspect extraction for online discussions using out-of-domain classification such as news articles and newsgroup documents. In this work, we introduce a simple approach based on sentence
Possible ways of mini-fullerene formation: from four to twenty
this it follows that the least fullerene has twenty atoms forming twelve pentagons. We have supposed
Twenty-first century clouds over Indo-European homelandsMallory J. P.
Twenty-first century clouds over Indo-European homelands [Электронный ресурс
Twenty-first century clouds over Indo-European homelands [Электронный ресурс
Twenty-four hour monitoring and self-monitoring of blood pressure: a new emphasis of efficient useTwenty-four hour monitoring and self-monitoring of blood pressure: a new emphasis of efficient use
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