H
Heiko Paulheim
Researcher at University of Mannheim
Publications - 267
Citations - 6909
Heiko Paulheim is an academic researcher from University of Mannheim. The author has contributed to research in topics: Linked data & Computer science. The author has an hindex of 35, co-authored 239 publications receiving 5629 citations. Previous affiliations of Heiko Paulheim include Zentrum für Europäische Wirtschaftsforschung & Technische Universität Darmstadt.
Papers
More filters
Make Embeddings Semantic Again
TL;DR: A claim is made for semantic embeddings and possible ideas towards their construction are discussed, which show superior performance in many tasks, including relation prediction, recommender systems, or the enrichment of predictive data mining tasks.
Proceedings ArticleDOI
Predicting incorrect mappings: a data-driven approach applied to DBpedia
Mariano Rico,Nandana Mihindukulasooriya,Dimitris Kontokostas,Heiko Paulheim,Sebastian Hellmann,Asunción Gómez-Pérez +5 more
TL;DR: This work proposes a data-driven method to detect incorrect mappings automatically by analyzing the information from both instance data as well as ontological axioms and concludes that the best model achieves 93% accuracy.
Proceedings Article
Towards Automatic Topical Classification of LOD Datasets
TL;DR: This paper investigates to which extent the topical classification of new LOD datasets can be automated using machine learning techniques and the existing annotations as supervision and investigates problems with the manual classification of datasets in the current LOD cloud.
Book ChapterDOI
Ontologies for User Interface Integration
TL;DR: This paper introduces a framework employing ontologies for integrating applications on the user interface level, and shows how this approach supports both the developer and the user (in terms of reduced development times) of integrated applications.
Gathering Alternative Surface Forms for DBpedia Entities.
TL;DR: It is proposed to propose filtering approaches that allowed boosting the precision from 75% to 85% for a random entity subset, and from 45% to more than 65% for the subset of popular entities.