Recursive Style Breach Detection with Multifaceted Ensemble Learning

17 Jun 2019Daniel KopevDimitrina ZlatkovaKristiyan MitovAtanas AtanasovMomchil HardalovIvan KoychevPreslav Nakov

We present a supervised approach for style change detection, which aims at predicting whether there are changes in the style in a given text document, as well as at finding the exact positions where such changes occur. In particular, we combine a TF.IDF representation of the document with features specifically engineered for the task, and we make predictions via an ensemble of diverse classifiers including SVM, Random Forest, AdaBoost, MLP, and LightGBM... (read more)

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