Giuseppe Rizzo

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In the line of our investigation of inductive methods for Semantic Web reasoning, we propose an alternative way for approximate ABox reasoning based on the evidence and the analogical principle of the nearest-neighbors. Once neighbors of a test individual are selected through some distance measures, a combination rule descending from the Dempster-Shafer(More)
In this paper, we tackle the problem of clustering individual resources in the context of the Web of Data, that is characterized by a huge amount of data published in a standard data model with a well-defined semantics based on Web ontologies. In fact, clustering methods offer an effective solution to support a lot of complex related activities, such as(More)
In the context of Semantic Web, one of the most important issues related to the class-membership prediction task (through inductive models) on ontological knowledge bases concerns the imbalance of the training examples distribution, mostly due to the heterogeneous nature and the incompleteness of the knowledge bases. An ensemble learning approach has been(More)
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