N-gram Based Text Classification According To Authorship
نویسنده
چکیده
Authorship attribution studies consider author's identification of an anonymous text. This is a long history problem with a great number of various approaches. Those ones based on n-grams single out by their performances and good results. A n-gram approach is language independent but the selection of a number n is actually not. The focus of this paper is determination of a set of optimal values for number n for specific task of classification of newspaper articles written in Serbian according to authorship. We combine two different algorithms: the first one is based on counting common n-grams and the another one is based on relative frequency of n-grams. Experimental results are obtained for pairs of n-gram and profile sizes and it can be concluded that for all profile sizes the best results are obtained for 3≤n≤7.
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