Zobrazeno 1 - 10
of 128
pro vyhledávání: '"Zimmermann, Antoine"'
Autor:
Calbimonte, Jean-Paul, Ciortea, Andrei, Kampik, Timotheus, Mayer, Simon, Payne, Terry R., Tamma, Valentina, Zimmermann, Antoine
Publikováno v:
Transactions on Graph Data and Knowledge, Vol 1, Iss 1, Pp 13:1-13:22 (2023)
In this position paper, we propose that Knowledge Graphs (KGs) are one of the prime approaches to support the programming of autonomous software systems at the knowledge level. From this viewpoint, we survey how KGs can support different dimensions o
Externí odkaz:
https://doaj.org/article/212e8dce956d48b18381975235662893
The openness and accessibility of the Web has contributed greatly to its worldwide adoption. Uniform Resource Identifiers (URIs) are used for resource identification on the Web. A resource on the Web can be described in many ways, which makes it diff
Externí odkaz:
http://arxiv.org/abs/2204.10097
Autor:
Kampik, Timotheus, Mansour, Adnane, Boissier, Olivier, Kirrane, Sabrina, Padget, Julian, Payne, Terry R., Singh, Munindar P., Tamma, Valentina, Zimmermann, Antoine
The study of autonomous agents has a long tradition in the Multiagent Systems and the Semantic Web communities, with applications ranging from automating business processes to personal assistants. More recently, the Web of Things (WoT), which is an e
Externí odkaz:
http://arxiv.org/abs/2202.02574
Autor:
Hogan, Aidan, Blomqvist, Eva, Cochez, Michael, d'Amato, Claudia, de Melo, Gerard, Gutierrez, Claudio, Gayo, José Emilio Labra, Kirrane, Sabrina, Neumaier, Sebastian, Polleres, Axel, Navigli, Roberto, Ngomo, Axel-Cyrille Ngonga, Rashid, Sabbir M., Rula, Anisa, Schmelzeisen, Lukas, Sequeda, Juan, Staab, Steffen, Zimmermann, Antoine
Publikováno v:
ACM Comput. Surv. 54(4): 71:1-71:37 (2021)
In this paper we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data. Afte
Externí odkaz:
http://arxiv.org/abs/2003.02320
Autor:
Giménez-García, José M., Duarte, Maísa, Zimmermann, Antoine, Gravier, Christophe, Hruschke Jr., Estevam R., Maret, Pierre
NELL is a system that continuously reads the Web to extract knowledge in form of entities and relations between them. It has been running since January 2010 and extracted over 50,000,000 candidate statements. NELL's generated data comprises all the c
Externí odkaz:
http://arxiv.org/abs/1804.05639
We address the problem of providing contextual information about a logical formula (eg provenance, date of validity, or confidence) and representing it within a logical system. In this case, it is needed to rely on a higher order or non standard form
Externí odkaz:
http://arxiv.org/abs/1709.04970
Annotating semantic data with metadata is becoming more and more important to provide information about the statements being asserted. While initial solutions proposed a data model to represent a specific dimension of meta-information (such as time o
Externí odkaz:
http://arxiv.org/abs/1609.07102
Autor:
Zimmermann, Antoine
On souhaite modéliser la sémantique d'un réseau de connaissances hétérogènes mises en correspondances. On suppose que ces réseaux sont représentés par un ensemble d'ontologies reliées entre elles par des alignements d'ontologies. Dans un co
Externí odkaz:
http://tel.archives-ouvertes.fr/tel-00341525
http://tel.archives-ouvertes.fr/docs/00/34/36/82/PDF/these-zimmermann.pdf
http://tel.archives-ouvertes.fr/docs/00/34/36/82/PDF/these-zimmermann.pdf
We describe a generic framework for representing and reasoning with annotated Semantic Web data, a task becoming more important with the recent increased amount of inconsistent and non-reliable meta-data on the web. We formalise the annotated languag
Externí odkaz:
http://arxiv.org/abs/1103.1255
Publikováno v:
SeReCo Summer Workshop 2023
SeReCo Summer Workshop 2023, Jul 2023, Waischenfeld, Germany
NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning
NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning, Jul 2023, Siena, Italy. pp.381-394
SeReCo Summer Workshop 2023, Jul 2023, Waischenfeld, Germany
NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning
NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning, Jul 2023, Siena, Italy. pp.381-394
International audience; Knowledge Graphs (KGs) are an essential component of neuro-symbolic AI. KG Embedding Models (KGEMs) are used to represent elements of a KG (its entities and relations) in a vector space, to enable efficient processing and reas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::aeb2c710473ba2ba35329177010322d0
https://hal-emse.ccsd.cnrs.fr/emse-04138834
https://hal-emse.ccsd.cnrs.fr/emse-04138834