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- W3093322910 abstract "In this paper the authors compare by classification quality different types of stylometric features: low-level features that include character-based and word-based ones, and high-level rhythm features. The authors classified texts into centuries with each feature type separately and their combinations applying four classifiers: Random Forest and AdaBoost meta-algorithms, a LSTM neural network, and a GRU neural network. The experiments with three text corpora in English, Russian, and French languages showed that combining rhythm features and low-level features significantly improved quality of classification by centuries. Besides, classification results allowed to compare the styles of writing in different languages from a point of view of structure of sentences." @default.
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- W3093322910 date "2020-09-01" @default.
- W3093322910 modified "2023-09-23" @default.
- W3093322910 title "The Influence of Different Stylometric Features on the Classification of Prose by Centuries" @default.
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- W3093322910 doi "https://doi.org/10.23919/fruct49677.2020.9211036" @default.
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