New Publication @ ESWC 2022

@INPROCEEDINGS{zahera2022tab2onto, 
    author = "Hamada M. Zahera, Stefan Heindorf, Stefan Balke, Jonas Haupt, 
              Martin Voigt, Carolin Walter, Fabian Witter
              and Axel-Cyrille Ngonga Ngomo", 
    title = "Tab2Onto: Unsupervised Semantification with Knowledge Graph Embeddings",
    booktitle = "The Semantic Web: ESWC 2022 Satellite Events", 
    year = "2022",
    series = "Springer"
}

“A large amount of data is generated every day by various systems and applications. In many cases, this data comes into a tabular format, which lacks semantic representation and poses new challenges in data modeling. It is necessary to elevate the data into a richer representation, such as a knowledge graph adhering to an ontology. This will assist in the development of data modeling and integration. We propose an unsupervised approach, Tab2Onto, for learning ontologies from tabular data using knowledge graph embeddings, clustering, and a human in the loop. We conduct a set of experiments to investigate our approach on a benchmarking dataset from a medical domain to learn ontology of diseases.”

Abstract

More information about the current development: http://tab2onto.dice-research.org