Abstract
This article introduces a security level classification methodology of confidential documents written in Turkish language. Internal documents of TUBITAK UEKAE, holding various security levels (unclassified-restricted-secret) were classified within a methodology using Support Vector Machines (SVM’s) [1] and naïve bayes classifiers [3][9]. To represent term-document relations a recommended metric “TF-IDF" [2] was chosen to construct a weight matrix. Turkic languages provide a very difficult natural language processing problem in comparison with English: “Stemming”. A Turkish stemming tool "zemberek" was used to find out the features without suffix. At the end of the article some experimental results and success metrics are projected.
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References
Cortes, C., Vapnik, V.: Support-vector Networks. Machine Learning 20, 273–297 (1995)
Joachims, T.: Text Categorization with Support Vector Machines: Learning with Many Relevant Features. In: Nédellec, C., Rouveirol, C. (eds.) ECML 1998. LNCS, vol. 1398. Springer, Heidelberg (1998)
Feldman, R., Sanger, J.: Text Mining Handbook. Cambridge University Press, Cambridge (2007)
Han, J.W., Kamber, M.: Data Mining Concept and Techniques, 2nd edn. (2007)
Alparslan, E., Bahsi, B., Karahoca, A.: Classification of Turkish News Documents Using Support Vector Machines. INISTA (2009)
Cooley, R.: Classification of News Stories Using Support Vector Machines. In: IJCAI Workshop on Text Mining (1999)
Eyheramendy, S., Lewis, D., Madigan, D.: On the Naive Bayes Model for Text Categorization (2003)
Ageev, M., Dobrov, V.: Support Vector Machine Parameter Optimization for Text Categorization. In: International Conference on Information Systems Technology and its Applications (2003)
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© 2010 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Alparslan, E., Bahsi, H. (2010). Security Level Classification of Confidential Documents Written in Turkish. In: Daras, P., Ibarra, O.M. (eds) User Centric Media. UCMEDIA 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 40. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12630-7_41
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DOI: https://doi.org/10.1007/978-3-642-12630-7_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12629-1
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