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Task Oriented Evaluation of Module Extraction Techniques

Task Oriented Evaluation of Module Extraction Techniques
Task Oriented Evaluation of Module Extraction Techniques
Ontology Modularization techniques identify coherent and often reusable regions within an ontology. The ability to identify such modules, thus potentially reducing the size or complexity of an ontology for a given task or set of concepts is increasingly important in the Semantic Web as domain ontologies increase in terms of size, complexity and expressivity. To date, many techniques have been developed, but evaluation of the results of these techniques is sketchy and somewhat ad hoc. Theoretical properties of modularization algorithms have only been studied in a small number of cases. This paper presents an empirical analysis of a number of modularization techniques, and the modules they identify over a number of diverse ontologies, by utilizing objective, task-oriented measures to evaluate the fitness of the modules for a number of statistical classification problems.
Palmisano, Ignazio
0d76daba-ac1d-44ee-9417-7076870b7b34
Tamma, Valentina
5b302cae-5ff6-4f29-afa7-6d9dc2f73329
Payne, Terry
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Doran, Paul
00225971-b083-444b-9566-8f3f86570591
Palmisano, Ignazio
0d76daba-ac1d-44ee-9417-7076870b7b34
Tamma, Valentina
5b302cae-5ff6-4f29-afa7-6d9dc2f73329
Payne, Terry
0bb13d45-2735-45a3-b72c-472fddbd0bb4
Doran, Paul
00225971-b083-444b-9566-8f3f86570591

Palmisano, Ignazio, Tamma, Valentina, Payne, Terry and Doran, Paul (2009) Task Oriented Evaluation of Module Extraction Techniques. The Eighth International Semantic Web Conference (ISWC'09).

Record type: Conference or Workshop Item (Paper)

Abstract

Ontology Modularization techniques identify coherent and often reusable regions within an ontology. The ability to identify such modules, thus potentially reducing the size or complexity of an ontology for a given task or set of concepts is increasingly important in the Semantic Web as domain ontologies increase in terms of size, complexity and expressivity. To date, many techniques have been developed, but evaluation of the results of these techniques is sketchy and somewhat ad hoc. Theoretical properties of modularization algorithms have only been studied in a small number of cases. This paper presents an empirical analysis of a number of modularization techniques, and the modules they identify over a number of diverse ontologies, by utilizing objective, task-oriented measures to evaluate the fitness of the modules for a number of statistical classification problems.

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More information

Published date: 2009
Venue - Dates: The Eighth International Semantic Web Conference (ISWC'09), 2009-01-01
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 267764
URI: https://eprints.soton.ac.uk/id/eprint/267764
PURE UUID: 285643eb-43dc-4bfe-b2a7-b45ed88e4c84

Catalogue record

Date deposited: 08 Aug 2009 13:46
Last modified: 16 Jul 2019 22:23

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Contributors

Author: Ignazio Palmisano
Author: Valentina Tamma
Author: Terry Payne
Author: Paul Doran

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