Erik Altman, Jovan Blanusa, et al.
NeurIPS 2023
Linked Open Data (LOD) has emerged as one of the largest collections of interlinked structured datasets on the Web. Although the adoption of such datasets for applications is increasing, identifying relevant datasets for a specific task or topic is still challenging. As an initial step to make such identification easier, we provide an approach to automatically identify the topic domains of given datasets. Our method utilizes existing knowledge sources, more specifically Freebase, and we present an evaluation which validates the topic domains we can identify with our system. Furthermore, we evaluate the effectiveness of identified topic domains for the purpose of finding relevant datasets, thus showing that our approach improves reusability of LOD datasets. © 2013 IEEE.
Erik Altman, Jovan Blanusa, et al.
NeurIPS 2023
Pavel Klavík, A. Cristiano I. Malossi, et al.
Philos. Trans. R. Soc. A
Conrad Albrecht, Jannik Schneider, et al.
CVPR 2025
Miao Guo, Yong Tao Pei, et al.
WCITS 2011