Automatic Domain Identification for Linked Open Data
Document Type
Conference Proceeding
Abstract
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.
Digital Object Identifier (DOI)
Publication Info
Published in 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2013, pages 205-212.
© 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technologies, IEEE
APA Citation
Lalithsena, S., Hitzler, P., Sheth, A. P., & Jain, P. (2013). Automatic Domain Identification for Linked Open Data. Proceedings of the 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technologies, 205-212.
https://doi.org/10.1109/WI-IAT.2013.206