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- Natural Language Processing
- Machine Learning
- Information Retrieval
- Text quality assessment
Salar is a researcher at the Quality and Usability Lab at
Technische Universitat Berlin working on natural language processing
applications in crowdsourcing.
His main interest is NLP and machine learning models. He received his bachelor degree from Shahrood University of Technology and master in information technology from AmirKabir University of Technology (Tehran Polytechnic).
Quality and Usability Lab
Deutsche Telekom Laboratories
D-10587 Berlin, Germany
Tel: +49 30 8353 58394
|Author||Naderi, Babak and Mohtaj, Salar and Karan, Karan and Möller, Sebastian|
|Title of Book||11th International Conference on Quality of Multimedia Experience (QoMEX 2019)|
|Abstract||Data-driven approaches towards readability assessment, using automated linguistic analysis and machine learning methods, is a viable road forward for readability rankings. This paper describes the development of an automated readability assessment estimator based on supervised learning algorithms over German text corpora. For this purpose, natural language processing tools are used to extract 73 linguistic features grouped in traditional, lexical and morphological features. Feature engineering approaches are employed to select informative features. Different supervised learning models are implemented, with the top-ranked features fed as input. The results obtained depict that Random Forest Regressor yielding best result (0.847) for RMSE measure.|