Improving agent interoperability through a memetic ontology alignment: A comparative study

Interoperability is a key problem in agent-based systems where different interacting computational entities negotiate to achieve a common goal. In last years, this interoperability issue has been faced by exploiting the concept of ontology that enables a single agent to model its knowledge by means of a semantic description of a domain of interest. However, ontology ability to enable a full interoperability can be limited by the so-called semantic heterogeneity problem which arises when some discrepancies exist among ontologies modeling the knowledge related to different agents. As consequence, in order to enable an effective knowledge exchange, an ontology alignment process is necessary to lead proprietary ontologies to a mutual agreement. Recently, some studies have successfully investigated the suitability of memetic algorithms to solve this complex task. However, memetic algorithms are influenced by some design issues arising from the different choices that can be taken to implement them. The aim of this paper is to compare the performances yielded by different memetic ontology alignment systems in order to individuate the most suitable hybrid evolutionary approach which enables a strong agent interoperability. The comparison among the considered approaches is performed by applying a statistical multiple comparison procedure on a collection of ontologies belonging to the well-known Ontology Alignment Evaluation Initiative (OAEI) benchmarks.

[1]  Jörg P. Müller,et al.  Agent-Based Technologies and Applications for Enterprise Interoperability , 2012, Lecture Notes in Business Information Processing.

[2]  Janez Demsar,et al.  Statistical Comparisons of Classifiers over Multiple Data Sets , 2006, J. Mach. Learn. Res..

[3]  M. Friedman.  The Use of Ranks to Avoid the Assumption of Normality Implicit in the Analysis of Variance , 1937 .

[4]  David J. Sheskin,et al.  Handbook of Parametric and Nonparametric Statistical Procedures , 1997 .

[5]  I ScottKirkpatrick.  Optimization by Simulated Annealing: Quantitative Studies , 1984 .

[6]  Silvana Castano,et al.  Ontology-based Interoperability Services for Semantic Collaboration in Open Networked Systems , 2006 .

[7]  James Smith,et al.  A tutorial for competent memetic algorithms: model, taxonomy, and design issues , 2005, IEEE Transactions on Evolutionary Computation.

[8]  Michel C. A. Klein,et al.  Ontology Evolution: Not the Same as Schema Evolution , 2004, Knowledge and Information Systems.

[9]  Christian Blum,et al.  Metaheuristics in combinatorial optimization: Overview and conceptual comparison , 2003, CSUR.

[10]  Giovanni Acampora,et al.  A hybrid evolutionary approach for solving the ontology alignment problem , 2012, Int. J. Intell. Syst..

[11]  A. Dickson.  On Evolution , 1884, Science.

[12]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[13]  Michael R. Genesereth,et al.  Logical foundations of artificial intelligence , 1987 .

[14]  Ronald R. Yager,et al.  On ordered weighted averaging aggregation operators in multicriteria decisionmaking , 1988, IEEE Trans. Syst. Man Cybern..

[15]  Michel Klein,et al.  Combining and relating ontologies: an analysis of problems and solutions , 2001, OIS@IJCAI.

[16]  Thomas R. Gruber,et al.  A translation approach to portable ontology specifications , 1993, Knowl. Acquis..

[17]  Kevin Kok Wai Wong,et al.  Classification of adaptive memetic algorithms: a comparative study , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[18]  Ronald R. Yager,et al.  On ordered weighted averaging aggregation operators in multicriteria decision-making , 1988 .

[19]  Erhard Rahm,et al.  A survey of approaches to automatic schema matching , 2001, The VLDB Journal.

[20]  C. J. van Rijsbergen,et al.  Information Retrieval , 1979, Encyclopedia of GIS.

[21]  Pablo Moscato,et al.  On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts : Towards Memetic Algorithms , 1989 .

[22]  S. Holm.  A Simple Sequentially Rejective Multiple Test Procedure , 1979 .

[23]  Jérôme Euzenat,et al.  Specification of a Common Framework for Characterizing Alignment , 2004 .

[24]  Stefanos D. Kollias,et al.  A String Metric for Ontology Alignment , 2005, SEMWEB.