Dr F. Hasibi (Faegheh)
Assistant professor - Data Science
My general research interest lies in the intersection of Information Retrieval and Natural Language Processing, with the primary aim to provide focused answers in response to user questions in search engines and conversational AI systems.
In particular, I am interested in utilizing knowledge graphs for semantic understanding of text in conversational and search systems.
- H. Joko and F. Hasibi. “Personal Entity, Concept, and Named Entity Linking in Conversations”, In proceedings of 31st ACM International Conference on Information and Knowledge Management (CIKM ’22), 2022. Full text
- G. Aydin, S. A. Tabatabaei, G. Tsatsaronis, F. Hasibi. “Find the Funding: Entity Linking with Incomplete Funding Knowledge Bases”, In proceedings of the 29th International Conference on Computational Linguistics (COLING '22), 2022. Full text
- E. J. Gerritse, F. Hasibi, and A. P. de Vries. “Entity-aware Transformers for Entity Search”, In proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’22), 2022. Full text
- M.J. van Hulst, F. Hasibi, K. Dercksen, K. Balog, A.P. de Vries,“REL: An Entity Linker Standing on the Shoulders of Giants“, In proceedings of 43rd international ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’20), 2020. Full text
- E.J. Gerritse, F. Hasibi, A.P. de Vries. “Graph-Embedding Empowered Entity Retrieval”, In Proceedings of the 42nd European Conference on Information Retrieval (ECIR ’20), 2020. Full text
- 2022 - 2027 LESSEN aims to make the chat technology accessible for languages and domains with relatively little training data. It focuses on developing data and compute efficient chat algorithms (based on the state-of-art neural methods) to offer safe and transparent task-oriented conversational agents. More information
- 2021 - Radboud Entity Linker (REL) is an open-source entity linking project that helps machine understanding of texts by connecting text to semi-structured information in the knowledge graphs (e.g., Wikipedia). The project focuses on making the entity linking technology usable for multilingual, formal, and informal texts, requiring only limited computational power. REL is aimed to operate on texts in a variety of languages and forms (e.g., long documents, queries, and conversations), in a reasonable time and using commonly available hardware. More information