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A new generation of applications offers insight into the Semantic Web's current and future challenges—as well as the opportunities it might provide for users and developers alike. A lthough research on integrating semantics with the Web started almost as soon as the Web was in place, a concrete Semantic Web—that is, a large-scale collection of distributed(More)
One of the key promises of the Semantic Web is its potential to enable and facilitate data interoperability. The ability of data providers and application developers to share and reuse ontologies is a critical component of this data interoperability: if different applications and data sources use the same set of well defined terms for describing their(More)
Nowadays, the increasing amount of semantic data available on the Web leads to a new stage in the potential of Semantic Web applications. However, it also introduces new issues due to the heterogeneity of the available semantic resources. One of the most remarkable is redundancy, that is, the excess of different semantic descriptions, coming from different(More)
Watson is a gateway to the Semantic Web: it collects, analyzes and gives access to ontologies and semantic data available online with the objective of supporting their dynamic exploitation by semantic applications. We report on the analysis of 25 500 ontologies and semantic documents collected by Watson, giving an account about the way semantic technologies(More)
While current approaches to ontology mapping produce good results by mainly relying on label and structure based similarity measures , there are several cases in which they fail to discover important mappings. In this paper we describe a novel approach to ontology mapping , which is able to avoid this limitation by using background knowledge. Existing(More)
The increased availability of online knowledge has led to the design of several algorithms that solve a variety of tasks by harvesting the Semantic Web, i.e., by dynamically selecting and exploring a multitude of online ontologies. Our hypothesis is that the performance of such novel algorithms implicitly provides an insight into the quality of the used(More)
In this paper we address the issue of identifying the concepts in an ontology, which best summarize what the ontology is about. Our approach combines a number of criteria, drawn from cognitive science, network topol-ogy, and lexical statistics. In the paper we show two versions of our algorithm, which have been evaluated against the results produced by(More)
Ontology evolution aims at maintaining an ontology up to date with respect to changes in the domain that it models or novel requirements of information systems that it enables. The recent industrial adoption of Semantic Web techniques, which rely on ontologies, has led to the increased importance of the ontology evolution research. Typical approaches to(More)
Problems with large monolithical ontologies in terms of reusability, scalability and maintenance have led to an increasing interest in modularization techniques for ontologies. Currently, existing work suffers from the fact that the notion of modularization is not as well understood in the context of ontologies as it is in software engineering. In this(More)