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Selecting potentially relevant records using re-identification methods

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Abstract

This work proposes re-identification algorithms to select records that are interesting from the point of view of giving new information. Instead of focusing on re-identified elements, we focus on non re-identified records (non linked records) as they are the ones that potentially supply new and relevant information. Moreover, these relevant characteristics can correspond to chances for improving the knowledge of a system.

To evaluate our approach, we have applied it to a example using publicly available data from the UCI repository. We have used the data of theionosphere data base to build a re-identification problem for 35 non-common variables.

We show that the use of a simple heuristic rule base can effectively select potentially interesting records.

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Authors and Affiliations

  1. Dept. Comput. Eng. and Maths-ETSE, Universitat Rovira i Virgili, Av Països Catalans 26, 43007, Tarragona, Catalonia, Spain

    Josep Domingo-Ferrer

  2. Institut d’Investigació en Intel-ligència Artificial-CSIC, Campus UAB s/n, 08193, Bellaterra, Catalonia, Spain

    Vicenç Torra

Authors
  1. Josep Domingo-Ferrer
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  2. Vicenç Torra
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Additional information

Josep Domingo-Ferrer: He is a Professor of Computer Science at University Rovira i Virgili, Tarragona, Catalonia, Spain. He received M.Sc. in Computer Science from the Autonomous University of Barcelona in 1988 (Outstanding Graduation Award) and Ph.D. in Computer Science in 1991. He also holds a M.Sc. in Mathematics. His research has been devoted to data security in a broad sense, including cryptography and inference control in statistical databases. He has authored over 100 scientific publications and holds two patents. He has led several competitively funded research projects, sponsored by the European Commission, the Spanish government and the U.S. government. He is a Senior Member of IEEE.

Vicenç Torra: He is an Associate Research Professor at the Artificial Intelligence Research Institut (CSIC), Bellaterra, Catalonia, Spain. He received BSc in 1991, MSc in 1992 and PhD in 1991 (in Computer Science).

His research is on Information Fusion and Approximated Reasoning (Fuzzy Systems) and applications to Statistical Disclosure Control and Information Retrieval. He has authored more than 40 papers in SCI journals and 60 in other conferences and books. He has edited a book on Information Fusion in Data Mining and written a book on Artificial Intelligence. He has led several (national and international) research projects. He is a Senior Member of IEEE and member of the board (2001-) of the European Society for Fuzzy Logic and Technology.

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Domingo-Ferrer, J., Torra, V. Selecting potentially relevant records using re-identification methods. New Gener Comput 22, 239–252 (2004). https://doi.org/10.1007/BF03040962

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  • DOI: https://doi.org/10.1007/BF03040962

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