Kleanthi Georgala
Kleanthi Georgala
AKSW, DICE Group, University of Leipzig
Verified email at informatik.uni-leipzig.de
Cited by
Cited by
An efficient approach for the generation of allen relations
K Georgala, MA Sherif, ACN Ngomo
Proceedings of the Twenty-second European Conference on Artificial …, 2016
Spam filtering: an active learning approach using incremental clustering
K Georgala, A Kosmopoulos, G Paliouras
Proceedings of the 4th international conference on web intelligence, mining …, 2014
MOCHA2018: The mighty storage challenge at ESWC 2018
K Georgala, M Spasić, M Jovanovik, V Papakonstantinou, C Stadler, ...
Semantic Web Evaluation Challenge, 3-16, 2018
Dynamic planning for link discovery
K Georgala, D Obraczka, ACN Ngomo
European Semantic Web Conference, 240-255, 2018
LIMES: A Framework for Link Discovery on the Semantic Web
ACN Ngomo, MA Sherif, K Georgala, MM Hassan, K Dreßler, K Lyko, ...
KI-Künstliche Intelligenz, 1-11, 2021
An evaluation of models for runtime approximation in link discovery
K Georgala, M Hoffmann, ACN Ngomo
Proceedings of the International Conference on Web Intelligence, 57-64, 2017
Record linkage in medieval and early modern text
K Georgala, B van der Burgh, M Meeng, A Knobbe
Population Reconstruction, 173-195, 2015
Using Machine Learning for Link Discovery on the Web of Data
ACN Ngomo, D Obraczka, K Georgala
Demos at the European Conference on Artificial Intelligence, 2016
LIGER–Link Discovery with Partial Recall
K Georgala, MA Sherif, ACN Ngomo
Ontology Matching, 87, 2020
Scalable Link Discovery for Modern Data-Driven Applications.
K Georgala
DC@ ISWC, 25-32, 2016
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