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A. Mountassir, Benbrahim, H., et Berrada, I., « The nearest centroid based on vector norms: A new classification algorithm for a new document representation model », Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8556 LNAI, p. 442-456, 2014.
A. Mountassir, « A novel model for Document Representation », in Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA, 2013.
A. Mountassir, Benbrahim, H., et Berrada, I., « Sentiment classification on arabic corpora: A preliminary cross-study », Document Numerique, vol. 16, p. 73-96, 2013.
A. Mountassir, Benbrahim, H., et Berrada, I., « Representing text documents in training document spaces: A novel model for document representation », Journal of Theoretical and Applied Information Technology, vol. 56, p. 30-39, 2013.
A. Mountassir, Benbrahim, H., et Berrada, I., « New under-sampling methods to address the problem of unbalanced sentiment classification: Application on Arabic datasets », International Journal of Information and Communication Technology, vol. 9, p. 64-77, 2016.
A. Mountassir, Benbrahim, H., et Berrada, I., « A cross-study of sentiment classification on arabic corpora », in Res. and Dev. in Intelligent Syst. XXIX: Incorporating Applications and Innovations in Intel. Sys. XX - AI 2012, 32nd SGAI Int. Conf. on Innovative Techniques and Applications of Artificial Intel., 2012, p. 259-272.
A. Mountassir, Benbrahim, H., et Berrada, I., « An empirical study to address the problem of unbalanced data sets in sentiment classification », in Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, 2012, p. 3298-3303.
A. Mountassir, Benbrahim, H., et Berrada, I., « Some methods to address the problem of unbalanced sentiment classification in an arabic context », in CiSt 2012 - Proceedings: 2012 Colloquium in Information Science and Technology, 2012, p. 43-48.
A. Mountassir, Benbrahim, H., et Berrada, I., « Addressing the problem of unbalanced data sets in sentiment analysis », in KDIR 2012 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval, 2012, p. 306-311.

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