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We present a way of building ontologies that proceeds in a bottom-up fashion, defining concepts as clusters of concrete XML objects. Our rough bottom-up ontologies are based on simple relations like association and inheritance, as well as on value restrictions, and can be used to enrich and update existing upper ontologies. Then, we show how automatically generated assertions based on our bottom-up ontologies can be associated with a flexible degree of trust by nonintrusively collecting user feedback in the form of implicit and explicit votes. Dynamic trust-based views on assertions automatically filter out imprecisions and substantially improve metadata quality in the long run.
Semantic Web, bottom-up ontology, ad hoc conceptualization, metadata extraction and maintenance, fuzzy clustering techniques, trusted assertions.

P. Ceravolo, M. Viviani and E. Damiani, "Bottom-Up Extraction and Trust-Based Refinement of Ontology Metadata," in IEEE Transactions on Knowledge & Data Engineering, vol. 19, no. , pp. 149-163, 2007.
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