Analysis of preprocessing methods on classification of Turkish texts
Dilara Torunoğlu, Erhan Cakirman, Murat Can Ganiz, Selim Akyokuş, Mustafa Zahid GÜRBÜZ · 2011
Preprocessing is an important task and critical step in information retrieval and text mining. The objective of this study is to analyze the effect of preprocessing methods in text classification on Turkish texts. We compiled two large datasets from Turkish newspapers using a crawler. On these compiled data sets and using two additional datasets, we perform a detailed analysis of preprocessing methods such as stemming, stopword filtering and word weighting for Turkish text classification on several different Turkish datasets. We report the results of extensive experiments.