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A Fuzzy Approach to the Characterization of Database Query Answers

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Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 611))

Abstract

This paper describes an approach helping users to better understand the results of their queries. These results are structured with a clustering algorithm and described using a personal vocabulary. The goal is to find what the elements of a cluster have in common that also differentiates them from the elements of the other clusters. The data considered for characterizing each cluster of answers are not limited to attributes used in the query, revealing unexpected correlations to the user. The originality of this work resides in the definition and use of fuzzy-set-based characterizations and their properties.

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References

  1. Amgoud, L., Prade, H., Serrut, M.: Flexible querying with argued answers. In: Proceedings of the 14th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2005), pp. 573–578, Reno, Nevada, USA (2005)

    Google Scholar 

  2. de Calmès, M., Dubois, D., Hüllermeier, E., Prade, H., Sedes, F.: Flexibility and fuzzy case-based evaluation in querying: an illustration in an experimental setting. Int. J. Uncertainty, Fuzziness Knowl. Based Syst. 11(1), 43–66 (2003)

    Article  MATH  Google Scholar 

  3. Gaasterland, T., Godfrey, P., Minker, J.: An overview of cooperative answering. J. Intell. Inf. Syst. 1(2), 123–157 (1992)

    Article  Google Scholar 

  4. Gaume, B., Navarro, E., Prade, H.: Clustering bipartite graphs in terms of approximate formal concepts and sub-contexts. Int. J. Comput. Intell. Syst. 6(6), 1125–1142 (2013)

    Article  Google Scholar 

  5. Herschel, M.: Wondering why data are missing from query results? Ask conseil why-not. In: He, Q., Iyengar, A., Nejdl, W., Pei, J., Rastogi, R. (eds.) CIKM, pp. 2213–2218. ACM (2013)

    Google Scholar 

  6. Koudas, N., Li, C., Tung, A.K.H., Vernica, R.: Relaxing join and selection queries. In: Proceedings of the 32nd International Conference on Very Large Data Bases, pp. 199–210 (2006). http://dl.acm.org/citation.cfm?id=1182635.1164146

  7. Krishnapuram, R., Joshi, A., Nasraoui, O., Yi, L.: Low-complexity fuzzy relational clustering algorithms for web mining. IEEE T. Fuzzy Syst. 9(4), 595–607 (2001)

    Article  Google Scholar 

  8. Lesot, M.-J., Revault d’Allonnes, A.: Credit-card fraud profiling using a hybrid incremental clustering methodology. In: Hüllermeier, E., Link, S., Fober, T., Seeger, B. (eds.) SUM 2012. LNCS, vol. 7520, pp. 325–336. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  9. Liu, B., Jagadish, H.V.: DataLens: making a good first impression. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, pp. 1115–1118 (2009)

    Google Scholar 

  10. Moreau, A., Pivert, O., Smits, G.: A clustering-based approach to the explanation of database query answers. In: Andreasen, T., et al. (eds.) FQAS 2015. AISC, vol. 400, pp. 307–319. Springer, Switzerland (2015)

    Chapter  Google Scholar 

  11. Roy, S., Suciu, D.: A formal approach to finding explanations for database queries. In: Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, SIGMOD 2014, pp. 1579–1590. ACM, New York (2014)

    Google Scholar 

  12. Smits, G., Pivert, O.: Linguistic and graphical explanation of a cluster-based data structure. In: Beierle, C., Dekhtyar, A. (eds.) SUM 2015. LNCS, vol. 9310, pp. 186–200. Springer, Heidelberg (2015)

    Chapter  Google Scholar 

  13. Zadeh, L.: Fuzzy sets. Inf. Control 8, 338–353 (1965)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgments

This work has been partially funded by the French DGE (Direction Générale des Entreprises) under the project ODIN (Open Data INtelligence).

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Authors and Affiliations

  1. Irisa – University of Rennes 1, Technopole Anticipa, 22305, Lannion Cedex, France

    Aurélien Moreau, Olivier Pivert & Grégory Smits

Authors
  1. Aurélien Moreau
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  2. Olivier Pivert
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  3. Grégory Smits
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Corresponding author

Correspondence to Aurélien Moreau .

Editor information

Editors and Affiliations

  1. INESC-ID,Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

    Joao Paulo Carvalho

  2. LIP 6, Université Pierre et Marie Curie, Paris, France

    Marie-Jeanne Lesot

  3. School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands

    Uzay Kaymak

  4. IDMEC,Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

    Susana Vieira

  5. LIP6, Université Pierre et Marie Curie, CNRS, Paris, France

    Bernadette Bouchon-Meunier

  6. Iona College, Machine Intelligence Institute, New Rochelle, New York, USA

    Ronald R. Yager

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© 2016 Springer International Publishing Switzerland

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Moreau, A., Pivert, O., Smits, G. (2016). A Fuzzy Approach to the Characterization of Database Query Answers. In: Carvalho, J., Lesot, MJ., Kaymak, U., Vieira, S., Bouchon-Meunier, B., Yager, R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2016. Communications in Computer and Information Science, vol 611. Springer, Cham. https://doi.org/10.1007/978-3-319-40581-0_27

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  • DOI: https://doi.org/10.1007/978-3-319-40581-0_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40580-3

  • Online ISBN: 978-3-319-40581-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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