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Context Dependent Semantic Granularity

Academic Article
Publication Date:
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.
Iris type:
01.01 Articolo in rivista
Keywords:
semantic granularity; ontology; semantic browsing; context
List of contributors:
DE MARTINO, Monica; Monti, Marina; Giannini, Franca; Albertoni, Riccardo
Authors of the University:
ALBERTONI RICCARDO
DE MARTINO MONICA
GIANNINI FRANCA
Handle:
https://iris.cnr.it/handle/20.500.14243/84198
Published in:
INTERNATIONAL JOURNAL OF DATA MINING, MODELLING AND MANAGEMENT
Journal
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URL

http://inderscience.metapress.com/content/j1txn37645208305/
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