Data mining evolved as a collection of applicative problems and efficient solution algorithms relative to rather peculiar problems, all focused on the discovery of relevant information hidden in databases of huge dimensions. In particular, one of the most investigated topics is the discovery of association rules. This work proposes a unifying model that enables a uniform description of the problem of discovering association rules. The model provides SQL-like operator, named MINE RULE, which is capable of expressing all the problems presented so far in the literature concerning the mining of association rules. We demonstrate the expressive power of the new operator by means of several examples, some of which are classical, while some others are fully original and correspond to novel and unusual applications. We also present the operational semantics of the operator by means of an extended relational algebra. 1 Introduction Data Mining is a novel research area that develops tech- Pe...

The paper discusses the issue of views in the Web context. We introduce a set of tools and languages for managing and restructuring data coming from the World Wide Web. We present a specific data model, called the Araneus Data Model, inspired to the structures typically present in Web sites. The model allows us to describe the scheme of a Web hypertext, in the spirit of databases. Based on the

We investigate data organization in the World Wide Web. In order to extend traditional database techniques to the Web, we concentrate on stvctved 14eb sevwvs, those servers (now very common) in which data are organized according to precise structures and pages present strong regularities. The paper introduces several tools for the management of structured servers. We present a page ov{ented data model, called the ARANEUS )(t( Jod, inspired to the structures typically present in these servers. The model allows us to describe the scheme of a structured server, in the spirit of databases. Then, we develop a view definition language, called the ARANEUS /{w L(ng(g, based on the notion of v{gat{o in the scheme. It has two features: first, it allows to build relational views of the Web, which can then be queried using any relational query language; second, it allows the definition of derived Web structures from relational views. This can be used to restructure query results and access them as an hypertext or to build derived servers.

Integrating existing relational databases with ontology-based systems is among the important research problems for the Semantic Web. We have designed a comprehensive framework called OntoGrate which combines a highly automatic mapping system, a logic inference engine, and several syntax wrappers that inter-operate with consistent semantics to answer ontology-based queries using the data from heterogeneous databases. There are several major contributions of our OntoGrate research: (i) we designed an ontology-based framework that provides a unified semantics for mapping discovery and query translation by transforming database schemas to Semantic Web ontologies; (ii) we developed a highly automatic ontology mapping system which leverages object reconciliation and multi-relational data mining techniques; (iii) we developed an inference-based query translation algorithm and several syntax wrappers which can translate queries and answers between relational databases and the Semantic Web. The testing results of our implemented OntoGrate system in different domains show that the large amount of data in relational databases can be directly utilized for answering Semantic Web queries rather than first converting all relational data into RDF or OWL. Keywords: Ontology-based information integration; ontology mapping; data mining; relational database; semantic web. 1.