Dr. Raji Ghawi
Phone: 089/ 907793 – 203
Alexander von Humboldt Stiftung
Raji Ghawi has been working since 2018 as a post-doctoral research fellow at the Chair of Computational Social Sciences at the Bavarian School of Policy of the Technical University of Munich. Previously, he worked as an affiliate researcher at the American University of Beirut, Lebanon, and as a lecturer at Al-Baath University in Syria. He earned his doctorate in 2010 on "Ontology-based Cooperation of Information Systems" at the Le2i Laboratoire Electronique of the Université de Bourgogne, France.
His research interests include ontologies and semantic web, database systems, information retrieval and text mining, process mining and social network analysis.
2019: Raji Ghawi and Jürgen Pfeffer, "Efficient Hyperparameter Tuning with Grid Search for Text Categorization using kNN Approach with BM25 Similarity", Open Computer Science Journal, Topical Issue on Intelligent Methods for Textual Information Retrieval, July 2019.
2019: Raji Ghawi and Jürgen Pfeffer, "Extracting Ego-Centric Social Networks from Linked Open Data", the IEEE/WIC/ACM International Conference on Web Intelligence (WI’19), Thessaloniki, Greece, October 2019.
2019: Raji Ghawi and Jürgen Pfeffer, "Mining Social Networks from Linked Open Data", 24th International Conference on Conceptual Structures (ICCS 2019), Marburg, Germany.
2019: Raji Ghawi. "On Repairing Referential Integrity Constraints in Relational Databases", 15th International Conference: Beyond Databases, Architectures and Structures (BDAS 2019), Ustroń, Poland.
2019: Raji Ghawi. "Interactive Decomposition of Relational Database Schemes using Recommendations", 15th International Conference: Beyond Databases, Architectures and Structures (BDAS 2019), Ustroń, Poland.
2018: Raji Ghawi, Mirco Schönfeld, and Jürgen Pfeffer. "Towards Semantic-based Social Network Analysis." 14th International IEEE Conference on Signal-Image Technologies and Internet-Based Systems (SITIS 2018). Las Palmas de Gran Canaria, Spain.
2016: Raji Ghawi. "Process Discovery using Inductive Miner and Decomposition." A submission to the Process Discovery Contest @ BPM2016. Technical Report, arXiv:1610.07989.