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Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Large Scale Matching Issues and Advances

Large Scale Matching Issues and Advances
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Author(s): Sana Sellami (LIRIS, France), Aicha-Nabila Benharkat (LIRIS, France) and Youssef Amghar (LIRIS, France)
Copyright: 2010
Pages: 17
Source title: Ontology Theory, Management and Design: Advanced Tools and Models
Source Author(s)/Editor(s): Faiez Gargouri (Higher Institute of Informatics and Multimedia of Sfax, Tunisia) and Wassim Jaziri (Higher Institute of Informatics and Multimedia of Sfax, Tunisia)
DOI: 10.4018/978-1-61520-859-3.ch009

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Abstract

Nowadays, the Information technology domains (semantic web, E-business, digital libraries, life science, etc) abound with a large variety of data (e.g. DB schemas, XML schemas, ontologies) and bring up a hard problem: the semantic heterogeneity. Matching techniques are called to overcome this challenge and attempts to align these data. In this chapter, the authors are interested in studying large scale matching approaches. They survey the techniques of large scale matching, when a large number of schemas/ontologies and attributes are involved. They attempt to cover a variety of techniques for schema matching called Pair-wise and Holistic, as well as a set of useful optimization techniques. They compare the different existing schema/ontology matching tools. One can acknowledge that this domain is on top of effervescence and large scale matching needs many more advances. Then the authors provide conclusions concerning important open issues and potential synergies of the technologies presented.

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