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STOP WORD DETECTION AS A BINARY CLASSIFICATION PROBLEM
2017
Journal:  
Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering
Author:  
Abstract:

In a wide group of languages, the stop words, which have only grammatical roles and not contributing to information content, may be simply exposed by their relatively higher occurrence frequencies. But, in agglutinative or inflectional languages, a stop word may be observed in several different surface forms due to the inflection producing noise. In this study, some of the well-known binary classification methods are employed to overcome the inflectional noise problem in stop word detection. The experiments are conducted on corpora of an agglutinative language, Turkish, in which the amount of inflection is high and a non-agglutinative language, English, in which the inflection is lower for stop words. The evaluations demonstrated that in Turkish corpus, the classification methods improve stop word detection with respect to frequency-based method. On the other hand, the classification methods applied on English corpora showed no improvement in the performance of stop word detection.

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Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering

Field :   Fen Bilimleri ve Matematik; Mühendislik; Sağlık Bilimleri

Journal Type :   Uluslararası

Metrics
Article : 648
Cite : 330
2023 Impact : 0.038
Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering