Zobrazeno 1 - 10
of 97
pro vyhledávání: '"Monticolo Davy"'
Autor:
Baustista Rodriguez Sandra, Marche Brunelle, Hamdani Fatima Ezzahra, Camargo Mauricio, Mayer Frédérique, Bachmann Christophe, Monticolo Davy
Publikováno v:
Sustainable Operations and Computers, Vol 1, Iss , Pp 13-27 (2020)
Within the aim of supporting territories to create more sustainable systems, road infrastructure plays a paramount role, not only because road shoulders represent a non-negligible land area, including their own biodiversity, but also because this rep
Externí odkaz:
https://doaj.org/article/84123591cb134f598c5cd58eb73e922f
Knowledge graph embedding models (KGEMs) developed for link prediction learn vector representations for entities in a knowledge graph, known as embeddings. A common tacit assumption is the KGE entity similarity assumption, which states that these KGE
Externí odkaz:
http://arxiv.org/abs/2312.10370
Knowledge graphs (KGs) have emerged as a prominent data representation and management paradigm. Being usually underpinned by a schema (e.g., an ontology), KGs capture not only factual information but also contextual knowledge. In some tasks, a few KG
Externí odkaz:
http://arxiv.org/abs/2309.03685
Knowledge graph embedding models (KGEMs) have gained considerable traction in recent years. These models learn a vector representation of knowledge graph entities and relations, a.k.a. knowledge graph embeddings (KGEs). Learning versatile KGEs is des
Externí odkaz:
http://arxiv.org/abs/2306.03659
Publikováno v:
International Journal for Simulation and Multidisciplinary Design Optimization, Vol 8, p A7 (2017)
Today, companies involved in product development in the “Industry 4.0” era, need to manage all the necessary information required in the product entire lifecycle, in order to optimize as much as possible the product-process integration. In this p
Externí odkaz:
https://doaj.org/article/cc096755480e4c03a2c5451f30db8ef5
Knowledge graph embedding models (KGEMs) are used for various tasks related to knowledge graphs (KGs), including link prediction. They are trained with loss functions that consider batches of true and false triples. However, different kinds of false
Externí odkaz:
http://arxiv.org/abs/2303.00286
Using knowledge graph embedding models (KGEMs) is a popular approach for predicting links in knowledge graphs (KGs). Traditionally, the performance of KGEMs for link prediction is assessed using rank-based metrics, which evaluate their ability to giv
Externí odkaz:
http://arxiv.org/abs/2301.05601
Publikováno v:
2018 14th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), Nov 2018, Las Palmas de Gran Canaria, Spain. pp.420-426
The project management field has the imperative to increase the project probability of success. Experts have developed several project management maturity models to assets and improve the project outcome. However, the current literature lacks of mode
Externí odkaz:
http://arxiv.org/abs/2009.09828
Publikováno v:
International Multi-Conference OCTA'2019 on Organization of Knowledge and Advanced Technologies, University of Tunis (Tunisia) & International scholarly society ISKO Maghreb, Feb 2020, Tunis (ALECSO), Tunisia. pp.6-17
This article is about an intelligent system to support ideas management as a result of a multi-agent system used in a distributed system with heterogeneous information as ideas and knowledge, after the results about an ontology to describe the meanin
Externí odkaz:
http://arxiv.org/abs/2009.05282
Publikováno v:
International Journal of Lean Six Sigma, 2021, Vol. 13, Issue 5, pp. 1025-1057.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJLSS-10-2020-0163