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Reflex-SMAS, a Complex Adaptive System: An Empirical Evaluation

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Book cover E-Technologies: Embracing the Internet of Things (MCETECH 2017)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 289))

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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.

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Authors and Affiliations

  1. Université du Québec à Montréal (UQAM), Montréal, Canada

    Hicham Assoudi & Hakim Lounis

Authors
  1. Hicham Assoudi
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  2. Hakim Lounis
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Correspondence to Hicham Assoudi or Hakim Lounis .

Editor information

Editors and Affiliations

  1. Université de Montréal, Montreal, Québec, Canada

    Esma Aïmeur

  2. University of Ottawa, Ottawa, Ontario, Canada

    Umar Ruhi

  3. Carleton University, Ottawa, Ontario, Canada

    Michael Weiss

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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

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  • DOI: https://doi.org/10.1007/978-3-319-59041-7_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59040-0

  • Online ISBN: 978-3-319-59041-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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