Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Carsten Felix Draschner"'
Autor:
Carsten Felix Draschner, Farshad Bakhshandegan Moghaddam, Claus Stadler, Jens Lehmann, Hajira Jabeen
Publikováno v:
CIKM
Proceedings of the 30th ACM International Conference on Information & Knowledge Management
Proceedings of the 30th ACM International Conference on Information & Knowledge Management
This paper presents DistRDF2ML, the generic, scalable, and distributed framework for creating in-memory data preprocessing pipelines for Spark-based machine learning on RDF knowledge graphs. This framework introduces software modules that transform l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8f1a0d8ab15b69e12bd216fe0c428f4
https://zenodo.org/record/7665860
https://zenodo.org/record/7665860
Publikováno v:
IEEE Fifth International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=r3c4b2081b22::231ca2e365077997d2a0380e0b98bd9c
Publikováno v:
Studies on the Semantic Web
Studies on the Semantic Web-Further with Knowledge Graphs
SEMANTiCS 2021
Studies on the Semantic Web-Further with Knowledge Graphs
SEMANTiCS 2021
The last decades have witnessed significant advancements in terms of data generation, management, and maintenance. This has resulted in vast amounts of data becoming available in a variety of forms and formats including RDF. As RDF data is represente
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a6a280e9055f660538a4ef047a3aac7e
https://doi.org/10.3233/ssw210036
https://doi.org/10.3233/ssw210036
Publikováno v:
2021 IEEE 15th International Conference on Semantic Computing (ICSC)
ICSC
ICSC
In this paper, we present DistSim, a Scalable Distributed in-Memory Semantic Similarity Estimation framework for Knowledge Graphs. DistSim provides a multitude of state-ofthe-art similarity estimators. We have developed the Similarity Estimation Pipe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4afaad787f19ae0797dc5aff81ef2505