Spam Filtering: an Active Learning Approach using Incremental Clustering. - Kleanthi Georgala; Aris Kosmopoulos; George Paliouras (WIMS, 2014)

Record Linkage in Medieval and Early Modern Text. - Kleanthi Georgala; Benjamin van der Burgh; Marvin Meeng; Arno J. Knobbe (Population Reconstruction, 2015)

An Efficient Approach for the Generation of Allen Relations. - Kleanthi Georgala; Mohamed Ahmed Sherif; Axel-Cyrille Ngonga Ngomo (ECAI, 2016)

Scalable Link Discovery for Modern Data-Driven Applications. - Kleanthi Georgala (DC@ISWC, 2016)

MOCHA2017: The Mighty Storage Challenge at ESWC 2017. - Kleanthi Georgala; Mirko Spasic; Milos Jovanovik; Henning Petzka; Michael Röder; Axel-Cyrille Ngonga Ngomo (SemWebEval@ESWC, 2017)

An evaluation of models for runtime approximation in link discovery. - Kleanthi Georgala; Michael Hoffmann 007; Axel-Cyrille Ngonga Ngomo (WI, 2017)

Dynamic Planning for Link Discovery. - Kleanthi Georgala; Daniel Obraczka; Axel-Cyrille Ngonga Ngomo (ESWC, 2018)

MOCHA2018: The Mighty Storage Challenge at ESWC 2018. - Kleanthi Georgala; Mirko Spasic; Milos Jovanovik; Vassilis Papakonstantinou; Claus Stadler; Michael Röder; Axel-Cyrille Ngonga Ngomo (SemWebEval@ESWC, 2018)

LIGER - link discovery with partial recall. - Kleanthi Georgala; Mohamed Ahmed Sherif; Axel-Cyrille Ngonga Ngomo (OM@ISWC, 2020)

Applying edge-counting semantic similarities to link discovery: scalability and accuracy. - Kleanthi Georgala; Mohamed Ahmed Sherif; Michael Röder; Axel-Cyrille Ngonga Ngomo (OM@ISWC, 2020)

LIMES: A Framework for Link Discovery on the Semantic Web. - Axel-Cyrille Ngonga Ngomo; Mohamed Ahmed Sherif; Kleanthi Georgala; Mofeed Mohamed Hassan; Kevin Dreßler; Klaus Lyko; Daniel Obraczka; Tommaso Soru (Künstliche Intell., 2021)

Time-efficient link discovery for data-driven applications. - Kleanthi Georgala (2021)