A novel feature extraction approach for text-based language identification: Binary patterns
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Tarih
2016
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Gazi Univ, Fac Engineering Architecture
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Language identification (LI), which is a major task in natural language processing, is the process of determining the language from a given content. In this paper, a novel approach, which is based on the probability of the use of the characters that have the similar orders with respect to their UTF-8 values, was proposed. In order to evaluate and validate the proposed approach, four datasets, which contain texts in different numbers of languages, were employed. In the proposed approach, the features that were exacted by one-dimensional local binary pattern (1D-LBP) method were classified by various machine learning methods. Achieved LI accuracies in each of four employed datasets were 86.20%, 92.75%, 100% and 89.77%, respectively. The results showed that the proposed approach yields high success rates and it is an efficient way of language identification.
Açıklama
Anahtar Kelimeler
Text-based language identification, one dimensional local binary patterns, natural language processing, feature extraction
Kaynak
Journal of The Faculty of Engineering and Architecture of Gazi University
WoS Q Değeri
Q4
Scopus Q Değeri
Q2
Cilt
31
Sayı
4
