Abstract
In this chapter, we discuss the features that are used for text representation while comparing them in vector space model, such as words or n-grams. We also present the possible values of these features: tf, idf, and tf-idf.
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Bibliography
Argamon, S., Juola, P.: Overview of the international authorship identification competition at PAN-2011. In: Proc. of 5th Int. Workshop on Uncovering Plagiarism, Authorship, and Social Software Misuse (2011)
Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. Addison-Wesley (1999)
Jiménez-Salazar, H., Pinto, D., Rosso, P.: Uso del punto de transición en la selección de términos índice para agrupamiento de textos cortos. Procesamiento del Lenguaje Natural, 35, pp. 383–390 (2005)
Manning, C., Schütze, H.: Foundations of Statistical Natural Language Processing. MIT Press, Cambridge, MA (1999)
Stamatatos, E.: A survey of modern authorship attribution methods. Journal of the American Society for information Science and Technology 60(3): 538–556 (2009)
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Sidorov, G. (2019). Vector Space Model for Texts and the tf-idf Measure. In: Syntactic n-grams in Computational Linguistics. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-030-14771-6_3
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DOI: https://doi.org/10.1007/978-3-030-14771-6_3
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