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- W69275742 abstract "Authorship identification was introduced as one of the important problems in the law and journalism fields and it is one of the major techniques in plagiarism detection. In this paper, to tackle the authorship verification problem, we propose a probabilistic distribution model to represent each document as a feature set to increase the interpretability of the results and features. We also introduce a distance measure to compute the distance between two feature sets. Finally, we exploit a KNN-based approach and a dynamic feature selection method to detect the features which discriminate the author’s writing style." @default.
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- W69275742 date "2014-01-01" @default.
- W69275742 modified "2023-09-27" @default.
- W69275742 title "Authorship Identification Using Dynamic Selection of Features from Probabilistic Feature Set" @default.
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- W69275742 doi "https://doi.org/10.1007/978-3-319-11382-1_13" @default.
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