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

Dragon: Decision Tree Learning for Link Discovery. - Daniel Obraczka; Axel-Cyrille Ngonga Ngomo (ICWE, 2019)

Knowledge Graph Completion with FAMER (DI2KG Challenge Winner). - Daniel Obraczka; Alieh Saeedi; Erhard Rahm (DI2KG@KDD, 2019)

DBpedia FlexiFusion the Best of Wikipedia > Wikidata > Your Data. - Johannes Frey; Marvin Hofer; Daniel Obraczka; Jens Lehmann 001; Sebastian Hellmann (ISWC (2), 2019)

Embedding-Assisted Entity Resolution for Knowledge Graphs. - Daniel Obraczka; Jonathan Schuchart; Erhard Rahm (KGCW@ESWC, 2021)

An Evaluation of Hubness Reduction Methods for Entity Alignment with Knowledge Graph Embeddings. - Daniel Obraczka; Erhard Rahm (KEOD, 2021)

EAGER: Embedding-Assisted Entity Resolution for Knowledge Graphs. - Daniel Obraczka; Jonathan Schuchart; Erhard Rahm (CoRR, 2021)

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)

Big Data Integration for Industry 4.0. - Daniel Obraczka; Alieh Saeedi; Victor Christen; Erhard Rahm (Digital Transformation, 2022)

Fast Hubness-Reduced Nearest Neighbor Search for Entity Alignment in Knowledge Graphs. - Daniel Obraczka; Erhard Rahm (SN Comput. Sci., 2022)

Kiez Benchmarking Knowledge Graph Embeddings. - Daniel Obraczka; Erhard Rahm (Zenodo, 2022)

Benchmark Datasets for Inductive Entity Alignment. - Daniel Obraczka; Max Berrendorf; Charles Tapley Hoyt; Michael Galkin; Erhard Rahm (Zenodo, 2022)

Benchmark Datasets for Inductive Entity Alignment. - Daniel Obraczka; Max Berrendorf; Charles Tapley Hoyt; Michael Galkin; Erhard Rahm (Zenodo, 2022)

Construction of Knowledge Graphs: State and Challenges. - Marvin Hofer; Daniel Obraczka; Alieh Saeedi; Hanna Köpcke; Erhard Rahm (CoRR, 2023)

Comparing Symbolic and Embedding-Based Approaches for Relational Blocking. - Daniel Obraczka; Erhard Rahm (EKAW, 2024)

Graph-based Active Learning for Entity Cluster Repair. - Victor Christen; Daniel Obraczka; Marvin Hofer; Martin Franke; Erhard Rahm (CoRR, 2024)

Comparing Symbolic and Embedding-Based Approaches for Relational Blocking (Artifacts). - Daniel Obraczka; Erhard Rahm (Zenodo, 2024)

Construction of Knowledge Graphs: Current State and Challenges. - Marvin Hofer; Daniel Obraczka; Alieh Saeedi; Hanna Köpcke; Erhard Rahm (Inf., 2024)

Graph Metrics-driven Record Cluster Repair meets LLM-based active learning. - Victor Christen; Daniel Obraczka; Marvin Hofer; Martin Franke; Erhard Rahm (ACM J. Data Inf. Qual., 2025)