It is well known how the use of additional knowledge, coded through ontologies, can improve the quality of the results obtained, in terms of user satisfaction, when seeking information on the web. The choice of a knowledge base, as long as it is reduced to small domains, is still manageable in a semi-automatic mode. However, in wider contexts, where a higher scalability is required, a fully automatic procedure is needed. In this paper, we show how a procedure to extract an ontology from a collection of documents can be completely automatised by making use of an optimization procedure. To this aim, we have defined a suitable fitness function and we have employed a Random Mutation Hill-Climbing algorithm to explore the solution space in order to evolve a near-optimal solution. The experimental findings show that our method is effective. © 2011 Springer-Verlag Berlin Heidelberg.

Clarizia, F., Greco, L., Napoletano, P. (2011). An adaptive optimisation method for automatic lightweight ontology extraction. In ENTERPRISE INFORMATION SYSTEMS (pp.357-371). Springer Verlag [10.1007/978-3-642-19802-1_25].

An adaptive optimisation method for automatic lightweight ontology extraction

NAPOLETANO, PAOLO
Ultimo
2011

Abstract

It is well known how the use of additional knowledge, coded through ontologies, can improve the quality of the results obtained, in terms of user satisfaction, when seeking information on the web. The choice of a knowledge base, as long as it is reduced to small domains, is still manageable in a semi-automatic mode. However, in wider contexts, where a higher scalability is required, a fully automatic procedure is needed. In this paper, we show how a procedure to extract an ontology from a collection of documents can be completely automatised by making use of an optimization procedure. To this aim, we have defined a suitable fitness function and we have employed a Random Mutation Hill-Climbing algorithm to explore the solution space in order to evolve a near-optimal solution. The experimental findings show that our method is effective. © 2011 Springer-Verlag Berlin Heidelberg.
No
paper
Scientifica
Lightweight ontology; Random mutation hill-climbing; Topicmodel; Business and International Management; Modeling and Simulation; Management Information Systems; Control and Systems Engineering; Information Systems; Information Systems and Management; Business, Management and Accounting (all)
English
International Conference on Enterprise Information Systems JUN 08-AUG 12
978-3-642-19801-4
http://www.springer.com/series/7911
Clarizia, F., Greco, L., Napoletano, P. (2011). An adaptive optimisation method for automatic lightweight ontology extraction. In ENTERPRISE INFORMATION SYSTEMS (pp.357-371). Springer Verlag [10.1007/978-3-642-19802-1_25].
Clarizia, F; Greco, L; Napoletano, P
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/78189
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