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A Lightweight Approach to Extract Interschema Properties from Structured, Semi-Structured and Unstructured Sources in a Big Data Scenario

Author

Listed:
  • Francesco Cauteruccio

    (Dipartimento di Matematica e Informatica, Università della Calabria, Via Pietro Bucci, 87036 Arcavacata di Rende, CS, Italy)

  • Paolo Lo Giudice

    (#x2020;Dipartimento di Ingegneria dell’Informazione, delle Infrastrutture e dell’Energia Sostenibile, Università Mediterranea di Reggio Calabria, Via dell’Università, 25 (già Salita Melissari), 89124 Reggio Calabria CF, Italy)

  • Lorenzo Musarella

    (#x2020;Dipartimento di Ingegneria dell’Informazione, delle Infrastrutture e dell’Energia Sostenibile, Università Mediterranea di Reggio Calabria, Via dell’Università, 25 (già Salita Melissari), 89124 Reggio Calabria CF, Italy)

  • Giorgio Terracina

    (Dipartimento di Matematica e Informatica, Università della Calabria, Via Pietro Bucci, 87036 Arcavacata di Rende, CS, Italy)

  • Domenico Ursino

    (#x2021;Dipartimento di Ingegneria dell’Informazione, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy)

  • Luca Virgili

    (#x2021;Dipartimento di Ingegneria dell’Informazione, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy)

Abstract

The knowledge of interschema properties (e.g., synonymies, homonymies, hyponymies and subschema similarities) plays a key role for allowing decision-making in sources characterized by disparate formats. In the past, wide amount and variety of approaches to derive interschema properties from structured and semi-structured data have been proposed. However, currently, it is esteemed that more than 80% of data sources are unstructured. Furthermore, the number of sources generally involved in an interaction is much higher than in the past. As a consequence, the necessity arises of new approaches to address the interschema property derivation issue in this new scenario. In this paper, we aim at providing a contribution in this setting by proposing an approach capable of uniformly extracting interschema properties from a huge number of structured, semi-structured and unstructured sources.

Suggested Citation

  • Francesco Cauteruccio & Paolo Lo Giudice & Lorenzo Musarella & Giorgio Terracina & Domenico Ursino & Luca Virgili, 2020. "A Lightweight Approach to Extract Interschema Properties from Structured, Semi-Structured and Unstructured Sources in a Big Data Scenario," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 849-889, May.
    • Handle: RePEc:wsi:ijitdm:v:19:y:2020:i:03:n:s0219622020500182
    DOI: 10.1142/S0219622020500182
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