Marco Viviani

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In this work we propose a fuzzy technique to compare XML documents belonging to a semi-structured flow and sharing a common vocabulary of tags. Our approach is based on the idea of representing documents as fuzzy bags and, using a measure of comparison, evaluating structural similarities between them. Then we suggest how to organize the extracted knowledge(More)
Metadata produced by members of a diverse community of peers tend to contain low-quality or even mutually inconsistent assertions. Trust values computed on the basis of users' feedback can improve metadata quality and reduce inconsistency, eliminating untrustworthy assertions. In this paper, we describe an approach to metadata creation and improvement,(More)
—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(More)
Merging related RSS news (coming from one or different sources) is beneficial for end-users with different backgrounds (journalists, economists, etc.), particularly those accessing similar information. In this paper, we provide a practical approach to both: measure the relatedness, and identify relationships between RSS elements. Our approach is based on(More)
In the field of multi-application personalization, several techniques have been proposed to support user modeling for user data management across different applications. Many of them are based on data reconciliation techniques often implying the concepts of static ontologies and generic user data models. None of them have sufficiently investigated two main(More)
Database outsourcing is becoming increasingly popular introducing a new paradigm, called database-as-a-service, where an en-crypted client's database is stored at an external service provider. Existing proposals for querying encrypted databases are based on the association , with each encrypted tuple, of additional indexing information obtained from the(More)