Abstract
We present in this paper an automatic summarization method of Arabic documents. This method is based on a numerical approach which uses a semi-supervised learning technique. The proposed method consists of two phases. The first one is the learning phase and the second is the use phase. The learning phase is based on the Support Vector Machine (SVM) algorithm. In order to evaluate our method, we conducted a comparative study that involves the results generated by our system AIS (Arabic Intelligent Summarizer) with that realized by a human expert. The obtained results are very encouraging and we plan to extend our evaluation on a larger corpus to ensure the performance of our system.
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Boudabous, M.M., Maaloul, M.H., Belguith, L.H. (2010). Digital Learning for Summarizing Arabic Documents. In: Loftsson, H., Rögnvaldsson, E., Helgadóttir, S. (eds) Advances in Natural Language Processing. NLP 2010. Lecture Notes in Computer Science(), vol 6233. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14770-8_10
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DOI: https://doi.org/10.1007/978-3-642-14770-8_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14769-2
Online ISBN: 978-3-642-14770-8
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