Lorenzo Genta

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The availability of large collections of linked data that can be accessed through public services and search endpoints requires methods and techniques for reducing the data complexity and providing high-level views of data contents defined according to users specific needs. To this end, a crucial step is the definition of data classification methods and(More)
This paper presents techniques for tailoring linked data exploration by relying on the use of high-level, intuitive organization structures called <i>in</i>Clouds (<i>in</i>formation Clouds). Techniques based on <i>content filtering</i> and <i>relevance filtering</i> are proposed for enabling a user to adjust the <i>in</i>Cloud visualization according to(More)
In the web of data, similarity recognition is the basis for a variety of resource-consuming activities and applications, including data recommendation, data aggregation, and data analysis. In this paper, we propose HMatch4, a novel instance matching algorithm for similarity recognition, which has been developed on the ground of our experience with HMatch3(More)
In this paper, we present the main achievements of the MI-Search project for " multi-web " information integration around topics relevant for urban users like for example city events and points of interest. In particular, we discuss the results of our experimental evaluation over a considered case study about the city of Milan as well as ongoing/future(More)
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