Context dependent semantic granularity
by Riccardo Albertoni, Elena Camossi, Monica De Martino, Franca Giannini, Marina Monti
International Journal of Data Mining, Modelling and Management (IJDMMM), Vol. 3, No. 2, 2011

Abstract: A fundamental issue to improve the accessibility to information resources is how to efficiently deal with huge amount(s) of data. In this respect, ontology driven techniques are expected to improve the overlap between the Cognitive Space applied by the user and the Information Space, which is defined by the information providers. In this paper we describe a powerful method to extract semantic granularities, which enable the navigation of a repository according to different levels of abstraction. In the formalisation we present, granularities are explicitly parameterised according to criteria induced by the context, which improves the method flexibility. Furthermore, the parameterisation assists the user allowing to formulate and refine the browsing criteria. Case studies are described to demonstrate how granularities ease the information sources browsing and to illustrate how they may vary according to the context. A validation of the cognitive principles behind the method is presented, together with the analysis of the results obtained by the experimentation.

Online publication date: Thu, 26-Feb-2015

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