Data integration is the problem of combining data residing at different sources, and providing the user with a unified view of these data. The problem of designing data integration systems is important in current real world applications, and is characterized by a number of issues

data

There has been a proliferation of proposed mental modules in an attempt to account for different cognitive functions but so far there has been no successful account of their integration. ACT-R (Anderson & Lebiere, 1998) has evolved into a theory that consists of multiple modules but also

and the diagrammatic technique is given. Some implications for data integrity, infor-mation retrieval, and data manipulation are discussed. The entity-relationship model can be used as a basis for unification of different views of data: t,he network model, the relational model, and the entity set model. Semantic

We consider the problem of building data integration systems when the data sources are webs of data, rather than sets of relations. Previous approaches to modeling data sources are inappropriate in this context because they do not capture the relationships between linked data and the need

We propose a measure of capital market integration arising from a conditional regime-switching model. Our measure allows us to describe expected returns in countries that are segmented from world capital markets in one part of the sample and become integrated later in the sample. We find that a

of discovery is not pre-determined, while for classification rule mining there is one and only one predetermined target. In this paper, we propose to integrate these two mining techniques. The integration is done by focusing on mining a special subset of association rules, called class association rules (CARs

The goal of the Tsimmis Project is to develop tools that facilitate the rapid integration of heterogeneous information sources that may include both structured and unstructured data. This paper gives an overview of the project, describing components that extract properties from unstructured objects

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We present the Lorel language, designed for querying semistructured data. Semistructured data is becoming more and more prevalent, e.g., in structured documents such as HTML and when performing simple integration of data from multiple sources. Traditional data models and query languages