Christopoulou, F. - NaCTeM Publications - Aigaion 2.0

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Vorname(n):	F.
Nachname(n):	Christopoulou

Christopoulou, F., Miwa, M. und Ananiadou, S., A Walk-based Model on Entity Graphs for Relation Extraction, in: Proceedings of ACL, Seiten 81-88, 2018

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Christopoulou, F., Tran, T. T., Sahu, S. K., Miwa, M. und Ananiadou, S., Adverse Drug Events and Medication Relation Extraction in EHRs with Ensemble Deep Learning Methods (2019), in: Journal of the American Medical Informatics Association(ocz101)

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Espinosa, K., Georgiadis, P., Christopoulou, F., Ju., M., Miwa, M. und Ananiadou, S., Comparing neural models for nested and overlapping biomedical event detection (2022), in: BMC Bioinformatics, 23(211)

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Christopoulou, F., Miwa, M. und Ananiadou, S., Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs, in: Proceedings of EMNLP 2019, Seiten 4927-4938, 2019

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Christopoulou, F., Miwa, M. und Ananiadou, S., Distantly Supervised Relation Extraction with Sentence Reconstruction and Knowledge Base Priors, in: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT), Seiten 11-26, 2021

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Sahu, S. K., Christopoulou, F., Miwa, M. und Ananiadou, S., Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network, in: Proceedings of ACL 2019, Seiten 4309-4316, 2019

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Inan, E., Thompson, P., Christopoulou, F., Yates, T. und Ananiadou, S., Knowledge Graph Enrichment of a Semantic Search System for Construction Safety, in: Intelligent Systems and Applications. IntelliSys 2022., Seiten 33-52, Springer, Cham, 2022

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Wang, K., Stevens, R., Alachram, H., Li, Y., Soldatova, L. N., King, R. D., Ananiadou, S., Schoene, A, Li, M., Christopoulou, F., Ambite, J. L., Matthew, J., Garg, S., Hermjakob, U., Marcu, D., Sheng, E., Beissbarth, T., Wingender, E., Galstyan, A., Gao, X., Chambers, B., Pan, W., Khomtchouk, B. B., Evans, J. A. und Rzhetsky, A., NERO: a biomedical named-entity (recognition) ontology with a large, annotated corpus reveals meaningful associations through text embedding (2021), in: npj systems biology and applications, 7(38)

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