Executable Knowledge Graph for Transparent Machine Learning in Welding Monitoring at Bosch
Author:
Affiliation:
1. Bosch Center for AI & Oslo Metropolitan University, Renningen, Germany
2. University of Oslo, Oslo, Norway
3. Bosch Center for AI & University of Oslo, Renningen, Germany
4. Oslo Metropolitan University, Oslo, Norway
Funder
OntoCommons
Dome4.0
DataCloud
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3511808.3557512
Reference7 articles.
1. M. Yahya B. Zhou et al. 2022. Towards generalized welding ontology in line with ISO and knowledge graph construction. In ESWC. Springer. M. Yahya B. Zhou et al. 2022. Towards generalized welding ontology in line with ISO and knowledge graph construction. In ESWC. Springer.
2. Z. Zheng et al. 2022. Executable Knowledge Graph for Machine Learning: A Bosch Case for Welding Monitoring. In ISWC. Z. Zheng et al. 2022. Executable Knowledge Graph for Machine Learning: A Bosch Case for Welding Monitoring. In ISWC.
3. Zhuoxun Zheng et al. 2022. ExeKG: Executable Knowledge Graph System for User-friendly Data Analytics. In CIKM. Zhuoxun Zheng et al. 2022. ExeKG: Executable Knowledge Graph System for User-friendly Data Analytics. In CIKM.
4. Z. Zheng , B. Zhou , and Others. 2022. Query-based industrial analytics over knowledge graphs with ontology reshaping . In ESWC. Springer . Z. Zheng, B. Zhou, and Others. 2022. Query-based industrial analytics over knowledge graphs with ontology reshaping. In ESWC. Springer.
5. B. Zhou Z. Zheng et al. 2022. The data value quest: a holistic semantic approach at Bosch. In ESWC. Springer 287--290. B. Zhou Z. Zheng et al. 2022. The data value quest: a holistic semantic approach at Bosch. In ESWC. Springer 287--290.
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