Invited paper: Sig.ma: Live views on the Web of Data
Web Semantics: Science, Services and Agents on the World Wide Web
Connecting the dots: a multi-pivot approach to data exploration
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
Interactive relationship discovery via the semantic web
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part I
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In this paper, we introduce the approach we are taking to generate a knowledge model for biomedical literature with the ultimate goal of improving information retrieval over our digital library and facilitating the discovery of hidden relationships across papers. Existing ontologies are brought together in order to facilitate the representation of sections in scientific literature and meaningful fragments within those previously identified sections. Our model makes it possible to localize meaningful pieces in sections across the entire digital library. In this way it is possible to, for instance, find similar papers in a highly accurate manner. We are initially working with the entire collection of PubMed Central. Our ultimate goal is to improve information retrieval over our digital library and facilitate the discovery of hidden relationships across papers.