Pareto optimization for multiobjective matching of geospatial ontologies

Author

Bharambe, Ujwala ; Durbha, Surya S. ; Kurte, Kuldeep ; Younan, Nicolas H. ; King, Roger L.

Author_Institution

Centre of Studies in Resource Eng., Indian Inst. of Technol. Bombay(IITB), Mumbai, India

fYear

2013

fDate

21-26 July 2013

Firstpage

1159

Lastpage

1162

Abstract

Geospatial information is different than conventional information. Harmonization is needed for interoperability and seamless access to data. Ontology matching is an emerging solution to achieve this harmonization. The input data of the Geospatial ontologies vary from the conventional ontologies and hence it is conceptualized in a different manner. There are two major obstacles for geoinformation fusion: heterogeneity and uncertainty. Heterogeneity is more prevalent and uncertainty is an unavoidable entity in geospatial domain. This paper explores a novel multi-objective algorithm for geospatial ontology matching. It uses Pareto ranking to sort the probable solution and derives the pareto front. This pareto front is used further to find the best match.

Keywords

Pareto optimisation; geophysics computing; ontologies (artificial intelligence); open systems; pattern matching; sensor fusion; Pareto front; Pareto optimization; Pareto ranking; geoinformation fusion; geospatial domain; geospatial information; geospatial ontology matching; harmonization; input data; interoperability; multiobjective algorithm; Atmospheric waves; Geospatial analysis; Interoperability; Ontologies; Pareto optimization; Semantics; Interoperability; Ontology Matching; Pareto Front; Pareto Ranking;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International

Conference_Location

Melbourne, VIC

ISSN

2153-6996

Print_ISBN

978-1-4799-1114-1

Type

conf

DOI

10.1109/IGARSS.2013.6721371

Filename

6721371