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Vol.5 , No. 1, Publication Date: Feb. 12, 2018, Page: 24-29
 into decision making in case of ambiguity. Our solution is based on decision theory and a MCA approach with a TOPSIS method. It allows the multi-solution classification of morpho-syntactical ambiguity cases in order to come out with the best performance and reduce the number of candidate solutions.&picture=http://www.aascit.org/aascit/decorators/img/journal/901.jpg)
| [1] | Youssef Hoceini, ARCHIPEL Laboratory, Tahri Mohammed University of Bechar, Béchar, Algeria; Faculty for Applied Science, Informatics Department, University of Oran1-Ahmed Benbella, Oran, Algeria. |
| [2] | Mustapha Guezouri, Faculty for Applied Science, Informatics Department, University of Oran1-Ahmed Benbella, Oran, Algeria. |
The aim of this paper is to present a combination of natural language processing and multi-criterion analysis in order to reach an effective analysis when dealing with linguistic data from various sources. The coexistence of these two concepts has allowed us, based on a set of actions and criteria, to develop a coherent system that integrates the entire process of textual data analysis (no-vowelezed Arabic texts) into decision making in case of ambiguity. Our solution is based on decision theory and a MCA approach with a TOPSIS method. It allows the multi-solution classification of morpho-syntactical ambiguity cases in order to come out with the best performance and reduce the number of candidate solutions.
Keywords
Arabic Morpho-syntactical Analysis, Disambiguation, Multi-criterion Approach, TOPSIS, Complete Aggregation
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