Pub Date : 1900-01-01DOI: 10.4018/978-1-61520-859-3.CH009
S. Sellami, A. Benharkat, Y. Amghar
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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Pub Date : 1900-01-01DOI: 10.4018/978-1-61520-859-3.CH014
A. Boubekeur, M. Malki, A. Chouarfia, M. Belarbi
Exchanged information on the Web becomes very important. Information research is therefore vague and slow. XML common language enriched by the metadata was insufficient. In order to satisfy the enormous number of users, it will be necessary to introduce the data semantics concept. This latter allows defining the semantic Web project also called “Web 2.0”. Web 2.0 uses the Artificial Intelligence (AI) tools especially Knowledge Engineering (KE) where ontology formalism was used. Moreover, some research works added functional level to the Web. On this level, Web services satisfy interoperability. Therefore, an explicit semantic annotation (Benslimane, Amar Bensaber, & Malki, 2004) is necessary to improve interoperation. In this AbsTRACT
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