Zobrazeno 1 - 10
of 140
pro vyhledávání: '"Jiménez-Ruiz, Ernesto"'
Autor:
Chen, Jiaoyan, Dong, Hang, Hastings, Janna, Jiménez-Ruiz, Ernesto, López, Vanessa, Monnin, Pierre, Pesquita, Catia, Škoda, Petr, Tamma, Valentina
Publikováno v:
Transactions on Graph Data and Knowledge, Vol 1, Iss 1, Pp 5:1-5:33 (2023)
The term life sciences refers to the disciplines that study living organisms and life processes, and include chemistry, biology, medicine, and a range of other related disciplines. Research efforts in life sciences are heavily data-driven, as they pr
Externí odkaz:
https://doaj.org/article/4ff40f5f488842c7a6167ec1eaade3d0
Autor:
Polleres, Axel, Pernisch, Romana, Bonifati, Angela, Dell'Aglio, Daniele, Dobriy, Daniil, Dumbrava, Stefania, Etcheverry, Lorena, Ferranti, Nicolas, Hose, Katja, Jiménez-Ruiz, Ernesto, Lissandrini, Matteo, Scherp, Ansgar, Tommasini, Riccardo, Wachs, Johannes
Publikováno v:
Transactions on Graph Data and Knowledge, Vol 1, Iss 1, Pp 11:1-11:59 (2023)
Openly available, collaboratively edited Knowledge Graphs (KGs) are key platforms for the collective management of evolving knowledge. The present work aims t o provide an analysis of the obstacles related to investigating and processing specifically
Externí odkaz:
https://doaj.org/article/e41255811dc4468882afba6d1e04163e
Knowledge Graphs (KG) are the backbone of many data-intensive applications since they can represent data coupled with its meaning and context. Aligning KGs across different domains and providers is necessary to afford a fuller and integrated represen
Externí odkaz:
http://arxiv.org/abs/2310.07417
NeSy4VRD is a multifaceted resource designed to support the development of neurosymbolic AI (NeSy) research. NeSy4VRD re-establishes public access to the images of the VRD dataset and couples them with an extensively revised, quality-improved version
Externí odkaz:
http://arxiv.org/abs/2305.13258
Investigating whether pre-trained language models (LMs) can function as knowledge bases (KBs) has raised wide research interests recently. However, existing works focus on simple, triple-based, relational KBs, but omit more sophisticated, logic-based
Externí odkaz:
http://arxiv.org/abs/2302.06761
Autor:
Petricek, Tomas, Burg, Gerrit J. J. van den, Nazábal, Alfredo, Ceritli, Taha, Jiménez-Ruiz, Ernesto, Williams, Christopher K. I.
Data wrangling tasks such as obtaining and linking data from various sources, transforming data formats, and correcting erroneous records, can constitute up to 80% of typical data engineering work. Despite the rise of machine learning and artificial
Externí odkaz:
http://arxiv.org/abs/2211.00192
Autor:
Myklebust, Erik Bryhn, Jimenez-Ruiz, Ernesto, Chen, Jiaoyan, Wolf, Raoul, Tollefsen, Knut Erik
Extrapolation of adverse biological (toxic) effects of chemicals is an important contribution to expand available hazard data in (eco)toxicology without the use of animals in laboratory experiments. In this work, we extrapolate effects based on a kno
Externí odkaz:
http://arxiv.org/abs/2210.15985
Autor:
Zheng, Zhuoxun, Zhou, Baifan, Zhou, Dongzhuoran, Cheng, Gong, Jiménez-Ruiz, Ernesto, Soylu, Ahmet, Kharlamo, Evgeny
Industrial analytics that includes among others equipment diagnosis and anomaly detection heavily relies on integration of heterogeneous production data. Knowledge Graphs (KGs) as the data format and ontologies as the unified data schemata are a prom
Externí odkaz:
http://arxiv.org/abs/2209.11089
Ontology Matching (OM) plays an important role in many domains such as bioinformatics and the Semantic Web, and its research is becoming increasingly popular, especially with the application of machine learning (ML) techniques. Although the Ontology
Externí odkaz:
http://arxiv.org/abs/2205.03447
Automating ontology construction and curation is an important but challenging task in knowledge engineering and artificial intelligence. Prediction by machine learning techniques such as contextual semantic embedding is a promising direction, but the
Externí odkaz:
http://arxiv.org/abs/2202.09791