Abstract
Authorship analysis process in which finding the author of unknown text when the history of the writing style of the author known. It can be viewed as a multi-class, single-mark content classification assignment. A lot of author identification problems had been created and solved with the different methods. Character and word n-gram are most commonly used methods for feature construction and participated in authorship identification task. In this paper, we point out the methodology of formation of word n-gram. The approach described in the paper does not depend on constant value n, the value of n changes according to the occurrence of word sequences. The methodology applied to the collection of text which is from the varied time domain. We used a dataset of 13 authors, whose text generation time is big. Dynamic value of n chosen to generate word sequence. In terms of accuracy, the result shows improvement as compared to the fixed value of n in word n-gram. We also explore the significance of the dynamic value of n on the occurrence of a specified set of consecutive words.
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Tamboli, M.S., Prasad, R.S. (2020). Authorship Identification with Multi Sequence Word Selection Method. In: Abraham, A., Cherukuri, A.K., Melin, P., Gandhi, N. (eds) Intelligent Systems Design and Applications. ISDA 2018 2018. Advances in Intelligent Systems and Computing, vol 940. Springer, Cham. https://doi.org/10.1007/978-3-030-16657-1_61
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DOI: https://doi.org/10.1007/978-3-030-16657-1_61
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