Exploiting Turkish Wikipedia as a semantic resource for text classification
|Exploiting Turkish Wikipedia as a semantic resource for text classification|
|Author(s)||Poyraz M., Ganiz M.C., Akyokus S., Gorener B., Kilimci Z.H.|
|Published in||INISTA 2012 - International Symposium on INnovations in Intelligent SysTems and Applications|
|Keyword(s)||semantic algorithms, text classification, textual data mining, turkish text classification, vikipedi, wikipedia (Extra: Text classification, Textual data, Turkish texts, vikipedi, Wikipedia, Algorithms, Data mining, Intelligent systems, Semantics, Websites, Information retrieval systems)|
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Exploiting Turkish Wikipedia as a semantic resource for text classification is a 2012 conference paper written in English by Poyraz M., Ganiz M.C., Akyokus S., Gorener B., Kilimci Z.H. and published in INISTA 2012 - International Symposium on INnovations in Intelligent SysTems and Applications.
Majority of the existing text classification algorithms are based on the "bag of words" (BOW) approach, in which the documents are represented as weighted occurrence frequencies of individual terms. However, semantic relations between terms are ignored in this representation. There are several studies which address this problem by integrating background knowledge such as WordNet, ODP or Wikipedia as a semantic source. However, vast majority of these studies are applied to English texts and to the date there are no similar studies on classification of Turkish documents. We empirically analyze the effect of using Turkish Wikipedia (Vikipedi) as a semantic resource in classification of Turkish documents. Our results demonstrate that performance of classification algorithms can be improved by exploiting Vikipedi concepts. Additionally, we show that Vikipedi concepts have surprisingly large coverage in our datasets which mostly consist of Turkish newspaper articles.
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