Abstract
We present a lightweight framework for processing uncertain emergent knowledge that comes from multiple resources with varying relevance. The framework is essentially RDF-compatible, but allows also for direct representation of contextual features (e.g., provenance). We support soft integration and robust querying of the represented content based on well-founded notions of aggregation, similarity and ranking. A proof-of-concept implementation is presented and evaluated within large scale knowledge-based search in life science articles.
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Nováček, V., Decker, S. (2009). Towards Lightweight and Robust Large Scale Emergent Knowledge Processing. In: Bernstein, A., et al. The Semantic Web - ISWC 2009. ISWC 2009. Lecture Notes in Computer Science, vol 5823. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04930-9_29
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DOI: https://doi.org/10.1007/978-3-642-04930-9_29
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