Abstract
Despite the profusion of approaches that were proposed to deal with the problem of the Automatic Schema Matching, yet the challenges and difficulties caused by the complexity and uncertainty characterizing both the process and the outcome of Schema Matching motivated us to investigate how bio-inspired emerging paradigm can help with understanding, managing, and ultimately overcoming those challenges.
In this paper, we explain how we approached Schema Matching as a Complex Adaptive System (CAS) and how we modeled it using the approach of Agent-Based Modeling and Simulation (ABMS) giving birth to a new tool (prototype) for schema matching called Reflex-SMAS.
This prototype was submitted to a set of experiments which aimed to demonstrate the viability of our approach to two main aspects: (i) effectiveness (increasing the quality of the found matchings) and (ii) efficiency (reducing the effort required for this efficiency). The results, came to demonstrate the viability of our approach, both in terms of effectiveness or that of efficiency.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Rahm, E., Bernstein, P.A.: A survey of approaches to automatic schema matching. VLDB J. 10(4), 334–350 (2001)
Bohannon, P., Elnahrawy, E., Fan, W., Flaster, M.: Putting context into schema matching. In: Proceedings of the 32nd International Conference on Very Large Data Bases, pp. 307–318 (2006)
Cross, V.: Uncertainty in the automation of ontology matching. In: Fourth International Symposium on Uncertainty Modeling and Analysis, ISUMA 2003, pp. 135–140 (2003)
Madhavan, J., Bernstein, P.A., Rahm, E.: Generic schema matching with cupid. VLDB 1, 49–58 (2001)
Villanyi, B., Martinek, P., Szamos, A.: Voting based fuzzy linguistic matching. In: 2014 IEEE 15th International Symposium on Computational Intelligence and Informatics (CINTI), pp. 27–32 (2014)
Duchateau, F., Bellahsene, Z.: Designing a benchmark for the assessment of schema matching tools. Open J. Databases OJDB 1(1), 3–25 (2014)
Zhang, C.J., Chen, L., Jagadish, H.V., Cao, C.C.: Reducing uncertainty of schema matching via crowdsourcing. Proc. VLDB Endow. 6(9), 757–768 (2013)
Viet, H.N.Q., Luong, H.X., Miklos, Z., Aberer, K., Quan, T.T.: A MAS negotiation support tool for schema matching. In: The Twelfth International Conference on Autonomous Agents and Multiagent Systems (2013)
Shvaiko, P., Euzenat, J.: Ontology matching: state of the art and future challenges. IEEE Trans. Knowl. Data Eng. 25(1), 158–176 (2013)
Peukert, E.: Process-based schema matching: from manual design to adaptive process construction (2013)
Peukert, E., Eberius, J., Rahm, E.: A self-configuring schema matching system. In: 2012 IEEE 28th International Conference on Data Engineering (ICDE), pp. 306–317 (2012)
Nian-Feng, W., Xing-Chun, D.: Uncertain schema matching based on interval fuzzy similarities. Int. J. Adv. Comput. Technol. 4(1) (2012)
Ngo, D., Bellahsene, Z.: YAM++: a multi-strategy based approach for ontology matching task. In: Teije, A., et al. (eds.) EKAW 2012. LNCS, vol. 7603, pp. 421–425. Springer, Heidelberg (2012). doi:10.1007/978-3-642-33876-2_38
Gong, J., Cheng, R., Cheung, D.W.: Efficient management of uncertainty in XML schema matching. VLDB J. — Int. J. Very Large Data Bases 21(3), 385–409 (2012)
Sarma, A.D., Dong, X.L., Halevy, A.Y.: Uncertainty in data integration and dataspace support platforms. In: Bellahsene, Z., Bonifati, A., Rahm, E. (eds.) Schema Matching and Mapping. Data-Centric Systems and Applications, pp. 75–108. Springer, Heidelberg (2011)
Gal, A.: Managing uncertainty in schema matching with Top-K schema mappings. In: Spaccapietra, S., Aberer, K., Cudré-Mauroux, P. (eds.) Journal on Data Semantics VI. LNCS, vol. 4090, pp. 90–114. Springer, Heidelberg (2006). doi:10.1007/11803034_5
Gal, A.: Uncertain schema matching. Synth. Lect. Data Manag. 3(1), 1–97 (2011)
Fortin, R.: Comprendre la complexité: introduction à La Méthode d’Edgar Morin. Presses Université Laval (2005)
North, M.J., Tatara, E., Collier, N.T., Ozik, J.: Visual agent-based model development with repast simphony, Technical report, Argonne National Laboratory (2007)
North, M.J.: R and Repast Simphony (2010)
Bär, D., Zesch, T., Gurevych, I.: DKPro similarity: an open source framework for text similarity. In: Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pp. 121–126 (2013)
R.C. Team, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (2012). Open Access Available https://cran.r-project.org (2011)
Remondino, M., Correndo, G.: Mabs validation through repeated execution and data mining analisys. Int. J. Simul. Syst. Sci. Technol. 7(6) (2006)
Bellahsene, Z., Bonifati, A., Duchateau, F., Velegrakis, Y.: On evaluating schema matching and mapping. In: Bellahsene, Z., Bonifati, A., Rahm, E. (eds.) Schema Matching and Mapping. Data-Centric Systems and Applications, pp. 253–291. Springer, Heidelberg (2011)
Do, H.-H., Rahm, E.: COMA: a system for flexible combination of schema matching approaches. In: Proceedings of the 28th International Conference on Very Large Data Bases, pp. 610–621 (2002)
Aumueller, D., Do, H.-H., Massmann, S., Rahm, E.: Schema and ontology matching with COMA++. In: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data, pp. 906–908 (2005)
Massmann, S., Raunich, S., Aumüller, D., Arnold, P., Rahm, E.: Evolution of the COMA match system. In: Proceedings of the International Semantic Web Conference, pp. 49–60 (2011)
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Assoudi, H., Lounis, H. (2017). Reflex-SMAS, a Complex Adaptive System: An Empirical Evaluation. In: Aïmeur, E., Ruhi, U., Weiss, M. (eds) E-Technologies: Embracing the Internet of Things . MCETECH 2017. Lecture Notes in Business Information Processing, vol 289. Springer, Cham. https://doi.org/10.1007/978-3-319-59041-7_19
Download citation
DOI: https://doi.org/10.1007/978-3-319-59041-7_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-59040-0
Online ISBN: 978-3-319-59041-7
eBook Packages: Computer ScienceComputer Science (R0)