SEMANTIC DATA CLOUDING OVER THE WEBS

Very often, for business or personal needs, users require to retrieve, in a very fast way, all the available relevant information about a focused target entity, in order to take decisions, organize business work, plan future actions. To answer this kind of “entity”- driven user needs, a huge multiplicity of web resources is actually available, coming from the Social Web and related user-centered services (e.g., news publishing, social networks, microblogging systems), from the Semantic Web and related ontologies and knowledge repositories, and from the conventional Web of Documents. The Ph.D. thesis is devoted to define the notion of in-cloud and a semantic clouding approach for the construction of in-clouds that works over the Social Web, the Semantic Web, and the Web of Documents. in-clouds are built for a target entity of interest to organize all relevant web resources, modeled as web data items, into a graph, on the basis of their level of prominence and reciprocal closeness. Prominence captures the importance of a web resource within the in-cloud, by distinguishing, also in a visual way “a la tagcloud”, how much relevant web resources are with respect to the target entity. The level of closeness between web resources is evaluated using matching and clustering techniques, with the goal of determining how similar web resources are to each other and with respect to the target entity.