64 citations · 160 across the 12 of their papers we have counts for
12 papers
A Critical Re-evaluation of Benchmark Datasets for (Deep) Learning-Based Matching Algorithms
George Papadakis, Nishadi Kirielle, Peter Christen +1
Entity resolution (ER) is the process of identifying records that refer to the same entities within one or across multiple databases. Numerous techniques have been developed to tac…
Pre-trained Embeddings for Entity Resolution: An Experimental Analysis [Experiment, Analysis & Benchmark]
Alexandros Zeakis, George Papadakis, Dimitrios Skoutas +1
Many recent works on Entity Resolution (ER) leverage Deep Learning techniques involving language models to improve effectiveness. This is applied to both main steps of ER, i.e., bl…
Three-dimensional Geospatial Interlinking with JedAI-spatial
Marios Papamichalopoulos, George Papadakis, George Mandilaras +3
Geospatial data constitutes a considerable part of (Semantic) Web data, but so far, its sources are inadequately interlinked in the Linked Open Data cloud. Geospatial Interlinking…
Generalized Supervised Meta-blocking (technical report)
Luca Gagliardelli, George Papadakis, Giovanni Simonini +2
Entity Resolution constitutes a core data integration task that relies on Blocking in order to tame its quadratic time complexity. Schema-agnostic blocking achieves very high recal…
How to reduce the search space of Entity Resolution: with Blocking or Nearest Neighbor search?
George Papadakis, Marco Fisichella, Franziska Schoger +3
Entity Resolution suffers from quadratic time complexity. To increase its time efficiency, three kinds of filtering techniques are typically used for restricting its search space:…
Bipartite Graph Matching Algorithms for Clean-Clean Entity Resolution: An Empirical Evaluation
George Papadakis, Vasilis Efthymiou, Emanouil Thanos +1
Entity Resolution (ER) is the task of finding records that refer to the same real-world entities. A common scenario is when entities across two clean sources need to be resolved, w…