Samira Ellouze

Also published as: Samira Walha Ellouze


2017

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Machine Learning Approach to Evaluate MultiLingual Summaries
Samira Ellouze | Maher Jaoua | Lamia Hadrich Belguith
Proceedings of the MultiLing 2017 Workshop on Summarization and Summary Evaluation Across Source Types and Genres

The present paper introduces a new MultiLing text summary evaluation method. This method relies on machine learning approach which operates by combining multiple features to build models that predict the human score (overall responsiveness) of a new summary. We have tried several single and “ensemble learning” classifiers to build the best model. We have experimented our method in summary level evaluation where we evaluate each text summary separately. The correlation between built models and human score is better than the correlation between baselines and manual score.

2013

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An Evaluation Summary Method Based on a Combination of Content and Linguistic Metrics
Samira Ellouze | Maher Jaoua | Lamia Hadrich Belguith
Proceedings of the International Conference Recent Advances in Natural Language Processing RANLP 2013

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An evaluation summary method based on combination of automatic and textual complexity metrics (Une méthode d’évaluation des résumés basée sur la combinaison de métriques automatiques et de complexité textuelle) [in French]
Samira Walha Ellouze | Maher Jaoua | Lamia Hadrich Belguith
Proceedings of TALN 2013 (Volume 2: Short Papers)