Selecting potentially relevant records using re-identification methods

Authors:
Josep Domingo-Ferrer;Vicenç Torra
Affiliations:
Dept. Comput. Eng. and Maths - ETSE, Universitat Rovira i Virgili, Av Països Catalans 26, 43007 Tarragona, Catalonia, Spain;Institut d'Investigació en Intel-ligència Artifical - CSIC, Campus UAB s/n, 08193 Bellaterra, Catalonia, Spain
Venue:
New Generation Computing
Year:
2004

Citing 5
Cited 0

On ordered weighted averaging aggregation operators in multicriteria decisionmaking

IEEE Transactions on Systems, Man and Cybernetics
Methodological Considerations on Chance Discovery

Proceedings of the Joint JSAI 2001 Workshop on New Frontiers in Artificial Intelligence
The Scope of Chance Discovery

Proceedings of the Joint JSAI 2001 Workshop on New Frontiers in Artificial Intelligence
The Role of Counterexamples in Discovery Learning Environment: Awareness of the Chance for Learning

Proceedings of the Joint JSAI 2001 Workshop on New Frontiers in Artificial Intelligence
Re-identifying register data by survey data using cluster analysis: an empirical study

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems

Quantified Score

Hi-index	0.00

Visualization

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 reidentified 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 the ionosphere data base to build a re-identification problem for 35 noncommon variables.We show that the use of a simple heuristic rule base can effectively select potentially interesting records.