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Approaches to Semantics in Knowledge Management

Approaches to Semantics in Knowledge Management
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Author(s): Cristiano Fugazza (University of Milan, Italy), Stefano David (Polytechnic University of Marche, Italy), Anna Montesanto (Polytechnic University of Marche, Italy) and Cesare Rocchi (Polytechnic University of Marche, Italy)
Copyright: 2009
Pages: 25
Source title: Database Technologies: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): John Erickson (University of Nebraska, Omaha, USA)
DOI: 10.4018/978-1-60566-058-5.ch019

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Abstract

There are different approaches to modeling a computational system, each providing different semantics. We present a comparison among different approaches to semantics and we aim at identifying which peculiarities are needed to provide a system with uniquely interpretable semantics. We discuss different approaches, namely, Description Logics, Artificial Neural Networks, and relational database management systems. We identify classification (the process of building a taxonomy) as common trait. However, in this chapter we also argue that classification is not enough to provide a system with a Semantics, which emerges only when relations among classes are established and used among instances. Our contribution also analyses additional features of the formalisms that distinguish the approaches: closed versus. open world assumption, dynamic versus. static nature of knowledge, the management of knowledge, and the learning process.

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