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Publications associées (60)
Ontology-based Knowledge Representation for Traditional Martial Arts
Sarah Irene Brutton Kenderdine, Yumeng Hou
Traditional martial arts are treasures of humanity's knowledge and critical carriers of sociocultural memories throughout history. However, such treasured practices have encountered various challenges in knowledge transmission and now feature many entries ...
2024ProGAP: Progressive Graph Neural Networks with Differential Privacy Guarantees
Daniel Gatica-Perez, Sina Sajadmanesh
Graph Neural Networks (GNNs) have become a popular tool for learning on graphs, but their widespread use raises privacy concerns as graph data can contain personal or sensitive information. Differentially private GNN models have been recently proposed to p ...
Assoc Computing Machinery2024Martial Arts MAsters Knowledge Graph (MA2KG) dataset release
Releasing the Martial Arts MAsters Knowledge Graph (MA2KG) dataset, including the core ontologies and RDF dataset, accompanied with scripts for developing the Martial Art MAsters Knowledge Graph (MA2KG). ...
EPFL Infoscience2023Brokering between tenants for an international materials acceleration platform
Giovanni Pizzi, Ivano Eligio Castelli, Francisco Fernando Ramirez
The efficient utilization of resources in accelerated materials science necessitates flexible, reconfigurable software-defined research workflows. We demonstrate a brokering approach to modular and asynchronous research orchestration to integrate multiple ...
CELL PRESS2023HIPE-2022 Shared Task Named Entity Datasets
Maud Ehrmann, Matteo Romanello
HIPE-2022 datasets used for the HIPE 2022 shared task on named entity recognition and classification (NERC) and entity linking (EL) in multilingual historical documents. HIPE-2022 datasets are based on six primary datasets assembled and prepared for the sh ...
2022Strong Heuristics for Named Entity Linking
Robert West, Akhil Arora, Marko Culjak, Andreas Oliver Spitz
Named entity linking (NEL) in news is a challenging endeavour due to the frequency of unseen and emerging entities, which necessitates the use of unsupervised or zero-shot methods. However, such methods tend to come with caveats, such as no integration of ...
ASSOC COMPUTATIONAL LINGUISTICS-ACL2022Deep MinCut: Learning Node Embeddings by Detecting Communities
Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Chi Thang Duong, Trung-Dung Hoang
We present Deep MinCut (DMC), an unsupervised approach to learn node embeddings for graph -structured data. It derives node representations based on their membership in communities. As such, the embeddings directly provide insights into the graph structure ...
ELSEVIER SCI LTD2022Fixed-wing micro UAV open data with digicam and raw INS/GNSS
Jan Skaloud, Davide Antonio Cucci, Kenneth Joseph Paul
We have recently released in the open domain data originating from a series of flights conducted with a fixed-wing micro UAV carrying high-quality small camera and navigation sensors. This data was previously used in several peer-reviewed publications. How ...
2021Applying Effective Data Modelling Approaches for the Creation of a Participatory Archive Platform
The development of a participatory archive platform such as the one being carried out for the PIA research project requires a flexible infrastructure allowing genuine data curation and a robust underlying data model. A strong assumption to achieve this is ...
2021