Abstract
This paper proposes a novel approach for enhancing document excerpts with semantic structures that are treated as first-class citizens, i.e., integrated at the system level. Providing support for semantics at the system level is in contrast with existing solutions that implement semantics as an add-on using intermediate descriptors. A framework and a toolset inspired by the Semantic Web Stack have been integrated into the Snippet System, an operating system environment that provides support for fine-grained representation and management of documents and the relationships that exist between arbitrary excerpts. The high granularity, combined with native support for semantics, is leveraged to alleviate some of the existing personal information management problems in terms of content retrieval and document engineering. The resulting framework offers some inherent advantages in terms of refined resource description, content and knowledge reuse along with self-contained documents that retain their metadata without depending on intermediate entities.
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Atashpendar, A., Kirsch, L., Botev, J., Rothkugel, S. (2013). A Native Approach to Semantics and Inference in Fine-Grained Documents. In: Takeda, H., Qu, Y., Mizoguchi, R., Kitamura, Y. (eds) Semantic Technology. JIST 2012. Lecture Notes in Computer Science, vol 7774. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37996-3_18
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DOI: https://doi.org/10.1007/978-3-642-37996-3_18
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