Classification Performance of the Different Stemming Methods
Yazarlar (4)
Öğr. Gör. Mehmet Balcı Selçuk Üniversitesi, Türkiye
Prof. Dr. Rıdvan Saraçoğlu Yüzüncü Yıl Üniversitesi, Türkiye
Prof. Dr. Şakir TAŞDEMİR Selçuk Üniversitesi, Türkiye
Doç. Dr. Adem Gölcük Karamanoğlu Mehmetbey Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(Uluslararası alan indekslerindeki dergilerde yayınlanan tam makale)
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| Dergi Adı | International Journal of Applied Mathematics, Electronics and Computers | ||
| Dergi Tarandığı Indeksler | Open Academic Journals Index, Global Impact Factor(GIF), Directory of Research Journals Indexing (DRJI), Google Scholar, Academic Resource Index(ResearchBib), Index Scientific Journals (ISJ) | ||
| Makale Dili | İngilizce | Basım Tarihi | 08-2015 |
| Cilt / Sayı / Sayfa | 3 / 3 / 208–210 | DOI | – |
| UAK Araştırma Alanları |
Yapay Zeka
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| Özet |
| Saving textual data and accessing them in many fields have become one of the basic problems nowadays. The usage of these data effectively is directly related to the development of storage and access tools that will be used. Therefore, software programs using different methods have been developed. One of the points that need to be taken into account is data classifying. Because using raw data in these classifying processes is harmful, finding the stem of the texts is useful. In this study, the successes of two different stemming algorithms in the text classifying are comparatively examined. |
| Anahtar Kelimeler |
