Omar ET-TARGUY

Omar ET-TARGUY

Postdoctoral researcher in AI

Publications

My research focuses on uncertainty reasoning, possibilistic conditioning, and spatial data fusion for infrastructure networks. Below is a selection of my peer-reviewed publications.

You can also find my articles on my Google Scholar profile.

Journal Articles

Analysis of the Syntactic Computation of Fagin-Halpern Conditioning in Possibilistic Logic

Published in International Journal of Approximate Reasoning, 2025

First complete syntactic formulation of FH-conditioning in possibility theory with efficient computational complexity.

Recommended citation: Et-Targuy, O., Benferhat, S., Delenne, C., Begdouri, A. (2025). Analysis of the Syntactic Computation of Fagin-Halpern Conditioning in Possibilistic Logic. International Journal of Approximate Reasoning.
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Dempster-Shafer theory for object matching under data imperfection constraints: Application to wastewater networks’ line matching

Published in Information Sciences, 2025

Application of Dempster-Shafer theory to wastewater network object matching under data imperfection.

Recommended citation: Belghaddar, Y., Begdouri, A., Chahinian, N., Seriai, A., Et-targuy, O., & Delenne, C. (2025). Dempster-Shafer theory for object matching under data imperfection constraints: Application to wastewater networks' line matching. Information Sciences, 122304.
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Conference Papers

A Graph-Based Approach for Representing Wastewater Networks from GIS Data: Ensuring Connectivity and Consistency

Published in International Conference on Intelligent Systems and Data Science (ISDS), 2023

Graph-based methodology for ensuring connectivity in wastewater network representations from GIS data.

Recommended citation: Et-Targuy, O., Begdouri, A., Benferhat, S., Delenne, C., Do, T. N., & Ma, T. T. (2023, October). A Graph-Based Approach for Representing Wastewater Networks from GIS Data: Ensuring Connectivity and Consistency. In International Conference on Intelligent Systems and Data Science (pp. 243-257). Singapore: Springer Nature Singapore.
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Syntactic computation of Fagin-Halpern conditioning in possibility theory

Published in 24th International Conference on Logic for Programming, Artificial Intelligence and Reasoning (LPAR), 2023

Syntactic computation approach for FH-conditioning in possibility theory.

Recommended citation: Et-Targuy, O., Begdouri, A., Benferhat, S., & Delenne, C. (2023, June). Syntactic computation of Fagin-Halpern conditioning in possibility theory. In Proceedings of 24th International Conference on Logic for Programming, Artificial Intelligence and Reasoning (pp. 164-146).
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Categorizing data imperfections for object matching in wastewater networks using belief theory

Published in International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD), 2022

Categorization of data imperfections in wastewater networks using belief theory for improved object matching.

Recommended citation: Et-targuy, O., Belghaddar, Y., Begdouri, A., Chahinian, N., Seriai, A., & Delenne, C. (2022, May). Categorizing data imperfections for object matching in wastewater networks using belief theory. In International Conference on Advanced Intelligent Systems for Sustainable Development (pp. 387-398). Cham: Springer Nature Switzerland.
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Workshops

Revising Weighted Knowledge Bases Using FH-Conditioning

Published in ENIGMA workshop co-located with KR 2023, 2023

Extension of FH-conditioning to weighted knowledge bases for belief revision.

Recommended citation: Et-Targuy, O., Begdouri, A., Benferhat, S., & Delenne, C. (2023, September). Revising Weighted Knowledge Bases Using FH-Conditioning. In ENIGMA workshop co-located with the 20th International Conference on Principles of Knowledge Representation and Reasoning (KR 2023).
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