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A Feature Selection-Based Method for an Ontological Enrichment Process in Geographic Knowledge Modelling

A Feature Selection-Based Method for an Ontological Enrichment Process in Geographic Knowledge Modelling
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Author(s): Mohamed Farah (ISAMM, Tunisia), Hafedh Nefzi (ISAMM, Tunisia) and Imed Riadh Farah (ISAMM, Tunisia)
Copyright: 2019
Pages: 20
Source title: Environmental Information Systems: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-7033-2.ch016

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Abstract

Nowadays, geographic information becomes too complex and abundant, thus recent research projects have been undertaken to make it manageable and exploitable. Ontologies are considered as a valuable support for geographic information representation. Building geographic ontologies could be viewed as an enrichment process. Alignment of concepts coming from different ontologies is central to the enrichment process and deeply affects the quality of the resulting ontology. The alignment of ontologies is based on using similarity measures. In the literature, there are many models for ontology alignment that mainly differ with respect to the similarity measures they use and the way they are combined. Most of the alignment methods do not deal with the problem of correlation between similarity measures. In this chapter, we address this issue to better decide which similarity measures we should consider to better assess the true similarity between concepts. Our proposal consists of using feature selection methods, in order to select a reduced set of relevant similarity measures.

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