Record Details

PART OF SPEECH TAGGING IN ROMANIAN TEXTS

International Journal of Advanced Statistics and IT&c for Economics and Life Sciences

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Title PART OF SPEECH TAGGING IN ROMANIAN TEXTS
 
Creator Circioroaba, Claudia
Stancu, Mihai
Morariu, Daniel
Volovici, Daniel
 
Description Identifying Parts of Speech (PoS) represents the process by which grammar tags containing their corresponding PoS are attached automatic to every word within a sentence. Since no word acts as just one single PoS—their syntactic value depending on the context they are used in—identifying parts of speech is not a trivial matter. In this paper we have taken into account two tagging methods, based on Naïve Bayes’ classifier probabilities and the occurring context of the word for which the PoS must be identified. We have called these methods Backward Naïve Bayes and Forward Naïve Bayes. For Romanian language, we have taken into account seven different PoS as: noun, verb, adjective, adverb, article, preposition plus the „and others” category. From conducted experiments, we have observed that identifying the PoS for a word based on the PoS for the previous word produces better results in all respects. We have studied each PoS separately and have concluded that there also are more easily identifiable PoS in Romanian as well: article, preposition, noun, verb; meanwhile the adjective and adverb are more problematic in identifying the PoS.
 
Publisher Lucia Blaga University of Sibiu
 
Contributor —
 
Date 2018-03-07
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://magazines.ulbsibiu.ro/ijasitels/index.php/IJASITELS/article/view/18
 
Source International Journal of Advanced Statistics and IT&C for Economics and Life Sciences; Vol 7, No 1 (2017): IJASITELS
L-2067-354X
2559-365X
 
Language eng
 
Relation http://magazines.ulbsibiu.ro/ijasitels/index.php/IJASITELS/article/view/18/20
 
Rights Copyright (c) 2018 International Journal of Advanced Statistics and IT&C for Economics and Life Sciences