| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 487311 | Procedia Computer Science | 2015 | 8 Pages |
Abstract
In this article we described the approach to achieving Telama analyzer (Towards Environmental-Learning Arabic-Morphological Analyzer): statistical approach based on the Hidden Markov Model (MMC) of Degree 2 and Trigrams. We describe the general algorithm and resources performed to accomplish the task of achieving the analyzer. This work also details the different experiments: the problem of analyzing the training corpus and selection of the set of labels. Finally, an evaluation of our segmentation system closes this stage of work on the morphological analysis of Arabic words, the results are very encouraging.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
