kumova metin, senem izmir university of economics - faculty of engineering - department of software engineering, İzmir, Turkey , karaoğlan, bahar ege university - international computer institute (ici), İzmir, Turkey

STOP WORD DETECTION AS A BINARY CLASSIFICATION PROBLEM

34421

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

346

Stop word , Content word , Binary classification , tf , idf

Anadolu University Journal of Science and Technology. A : Applied Sciences and Engineering

359