Abstract
In this invited talk I will argue that to build scalable, transparent and explainable AI in various domains where heterogeneous data is available, we need to collaborate with domain experts to develop relevant and high-quality knowledge graphs as well as appropriate data science and Machine Learning methods to constantly enrich and analyse these graphs. I give examples in the Digital Humanities and Internet of Things.
Original language | English |
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Title of host publication | SEMPDW 2022 Posters, Demos and Workshops at SEMANTiCS 2022 |
Subtitle of host publication | Proceedings of Poster and Demo Track and Workshop Track of the 18th International Conference on Semantic Systems co-located with 18th International Conference on Semantic Systems (SEMANTiCS 2022) Vienna, Austria, September 13th to 15th, 2022 |
Editors | Umutkan Şimşek, David Chaves-Fraga, Tassilo Pellegrini, Sahar Vahdat |
Publisher | CEUR-WS |
Number of pages | 2 |
Publication status | Published - 2022 |
Event | 18th International Conference on Semantic Systems, SEMPDW 2022 - Vienna, Austria Duration: 13 Sept 2022 → 15 Sept 2022 |
Publication series
Name | CEUR Workshop Proceedings |
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Publisher | CEUR Workshop Proceedings |
Volume | 3235 |
ISSN (Print) | 1613-0073 |
Conference
Conference | 18th International Conference on Semantic Systems, SEMPDW 2022 |
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Country/Territory | Austria |
City | Vienna |
Period | 13/09/22 → 15/09/22 |
Bibliographical note
Publisher Copyright:© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)