Study about Arabic Text Documents Classification using Ontologies
published by Aِl-Baath University
in 2014
in
and research's language is
العربية
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Abstract in English
In this paper, we introduce an algorithm for grouping Arabic
documents for building an ontology and its words. We execute
the algorithm on five ontologies using Java. We manage the
documents by getting 338667 words with its weights
corresponding to each ontology. The algorithm had proved its
efficiency in optimizing classifiers (SVM, NB) performance, which
we tested in this study, comparing with former classifiers results
for Arabic language.
References used
AL-Ghuribi,S Alshomrani,S. 2014. Bi-languages mining algorithm for classifying text documents (BiLTc), International Jornal of Academic Research Part A Vol. 6 No. 5, 16-25
Gruber,T. 1993. A translation approach to providing portable ontology specifications, Knowledge Acquisition, Vol.5 No 2, 199-220
Hastie,T Tibshirani,R Friedman.J. 2013-The elements of Statistical Learning - Data Mining, Inference, and Prediction. Springer-Verlag, second Ed, Berlin,764p