Abstract
Named entities (NE) are words that refer to names of people, locations, organization, etc. NE are present in every kind of documents: e-mails, letters, essays, novels, poems. Automatic detection of these words is very important task in natural language processing. Sometimes, NE are used in authorship attribution studies as a stylometric feature. The goal of this paper is to evaluate the effect of the presence of NE in texts for the authorship attribution task: are we really detecting the style of an author or are we just discovering the appearance of the same NE. We used the corpus that consists of 91 novels of 7 authors of XVIII century. These authors spoke and wrote English, their native language. All novels belong to fiction genre. The used stylometric features were character n-grams, word n-gram and n-gram of POS tags of various sizes (2-grams, 3-grams, etc.). Five novels were selected for each author, these novels contain between 4 and 7% of the NE. All novels were divided into blocks, each block contains 10,000 terms. Two kinds of experiment were conducted: automatic classification of blocks containing NE and of the same blocks without NE. In some cases, we use only the most frequent n-grams (500, 2,000 and 4,000 n-grams). Three machine learning algorithms were used for classification task: NB, SVM (SMO) and J48. The results show that as a tendency the presence of the NE helps to classify (improvements from 5% to 20%), but there are specific authors when NE do not help and even make the classification worse (about 10% of experimental data).
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Acknowledgements
We would like to thank the support of Mexican government (CONACYT project 240844, SNI, SIP IPN projects 20161947, 20161958).
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Ríos-Toledo, G., Sidorov, G., Castro-Sánchez, N.A., Nava-Zea, A., Chanona-Hernández, L. (2017). Relevance of Named Entities in Authorship Attribution. In: Sidorov, G., Herrera-Alcántara, O. (eds) Advances in Computational Intelligence. MICAI 2016. Lecture Notes in Computer Science(), vol 10061. Springer, Cham. https://doi.org/10.1007/978-3-319-62434-1_1
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