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A Possibilistic Valid-Time Model

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Advances on Computational Intelligence (IPMU 2012)

Abstract

Information in databases can be imperfect and this imperfection has several forms and causes. In some cases, a single value should be stored, but it is (partially) unknown. The uncertainty about which value to store leads to the aforementioned imperfection. In temporal databases, uncertainty can arise, concerning which temporal notion needs to be stored. Because in temporal databases, temporal notions influence the consistency with which the database models the reality, this uncertainty has a direct impact on the consistency of the model. To represent this temporal uncertainty, previous works have adapted fuzzy sets with conjunctive interpretation, an approach that might prove misleading. This work presents a model that represents the uncertainty using possibility and necessity measures, which are fuzzy sets with disjunctive interpretations.

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References

  1. Allen, J.F.: Maintaining knowledge about temporal intervals. Commun. ACM 26, 832–843 (1983)

    Article  MATH  Google Scholar 

  2. Billiet, C., Pons, J.E., Matthé, T., De Tré, G., Pons Capote, O.: Bipolar Fuzzy Querying of Temporal Databases. In: Christiansen, H., De Tré, G., Yazici, A., Zadrozny, S., Andreasen, T., Larsen, H.L. (eds.) FQAS 2011. LNCS (LNAI), vol. 7022, pp. 60–71. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  3. Bohlen, M., Busatto, R., Jensen, C.: Point-versus interval-based temporal data models. In: Proceedings of 14th Int. Conf. on Data Engineering 1998, pp. 192–200 (1998)

    Google Scholar 

  4. Bolour, A., Anderson, T.L., Dekeyser, L.J., Wong, H.K.T.: The role of time in information processing: a survey. ACM SIGMOD Record 12, 27–50 (1982)

    Article  Google Scholar 

  5. Bosc, P., Pivert, O.: Modeling and querying uncertain relational databases: A survey of approaches based on the possible worlds semantics. Int. J. Uncertainty Fuzziness Knowlege-Based Syst. 18(5), 565–603 (2010)

    Article  MathSciNet  Google Scholar 

  6. Van der Cruyssen, B., De Caluwe, R., De Tré, G.: A theoretical fuzzy time model based on granularities. In: Proceedings of the 5th European Congress on Intelligent Techniques and Soft Computing, pp. 1127–1131. ELITE Foundation (1997)

    Google Scholar 

  7. Dekhtyar, A., Ross, R., Subrahmanian, V.S.: Probabilistic temporal databases, i: algebra. ACM Trans. Database Syst. 26, 41–95 (2001)

    Article  MATH  Google Scholar 

  8. Dubois, D., HadjAli, A., Prade, H.: Fuzziness and uncertainty in temporal reasoning. Journal of Universal Computer Science 9(9), 1168–1194 (2003)

    MathSciNet  Google Scholar 

  9. Dubois, D., Prade, H.: Ranking fuzzy numbers in the setting of possibility theory. Information Sciences 30, 183–224 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  10. Dubois, D., Prade, H.: Possibility Theory: An Approach to Computerized Processing of Uncertainty. Plenum Press, New York (1988)

    MATH  Google Scholar 

  11. Dubois, D., Prade, H.: Processing fuzzy temporal knowledge. IEEE Transactions on Systems, Man, and Cybernetics 19, 729–744 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  12. Dyreson, C., Grandi, F., et al.: A consensus glossary of temporal database concepts. SIGMOD Rec. 23, 52–64 (1994)

    Article  Google Scholar 

  13. Galindo, J., Medina, J.M., Pons, O., Cubero, J.C.: A Server for Fuzzy SQL Queries. In: Andreasen, T., Christiansen, H., Larsen, H.L. (eds.) FQAS 1998. LNCS (LNAI), vol. 1495, pp. 164–174. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  14. Garrido, C., Marin, N., Pons, O.: Fuzzy intervals to represent fuzzy valid time in a temporal relational database. Int. J. Uncertainty Fuzziness Knowlege-Based Syst. 17, 173–192 (2009)

    Article  MATH  Google Scholar 

  15. Jensen, C.S., Mark, L., Roussopoulos, N.: Incremental implementation model for relational databases with transaction time. IEEE Trans. Knowl. Data Eng. 3, 461–473 (1991)

    Article  Google Scholar 

  16. Jensen, C.S., Snodgrass, R.T., Soo, M.D.: The tsql2 data model. In: The TSQL2 Temporal Query Language, pp. 153–238 (1995)

    Google Scholar 

  17. Lin, H. (codirector), C.J., Bohlen, M., Busatto, R., Gregersen, H., Torp, K. (codirector), R.S., Datta, A., Ram, S.: Efficient conversion between temporal granularities. Master’s thesis, The University of Arizona (1997)

    Google Scholar 

  18. Medina, J.M., Pons, O., Cubero, J.C.: Gefred. a generalized model of fuzzy relational databases. Information Sciences 76, 87–109 (1994)

    Article  Google Scholar 

  19. Nascimento, M.A., Eich, M.H.: Decision time in temporal databases. In: Proceedings of the 2nd Int. Workshop on Temporal Representation and Reasoning, pp. 157–162 (1995)

    Google Scholar 

  20. Ohlbach, H.J.: Relations between fuzzy time intervals. In: International Symposium on Temporal Representation and Reasoning, pp. 44–51 (2004)

    Google Scholar 

  21. Parisi, F., Parker, A., Grant, J., Subrahmanian, V.S.: Scaling Cautious Selection in Spatial Probabilistic Temporal Databases. In: Jeansoulin, R., Papini, O., Prade, H., Schockaert, S. (eds.) Methods for Handling Imperfect Spatial Information. STUDFUZZ, vol. 256, pp. 307–340. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  22. Pons, J.E., Bronselaer, A., De Tré, G., Pons, O.: Possibilistic evaluation of sets, Submitted to the Int. J. Uncertainty Fuzziness Knowlege-Based Syst. (2011)

    Google Scholar 

  23. Schockaert, S., De Cock, M., Kerre, E.E.: Fuzzifying allen’s temporal interval relations. IEEE Transactions on Fuzzy Systems 16(2), 517–533 (2008)

    Article  Google Scholar 

  24. Snodgrass, R.: The temporal query language tquel. In: Proceedings of the 3rd ACM SIGACT-SIGMOD, pp. 204–213. ACM, New York (1984)

    Google Scholar 

  25. Zadeh, L.A.: Fuzzy sets. Information and Control 8, 338–353 (1965)

    Article  MathSciNet  MATH  Google Scholar 

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Pons, J.E., Billiet, C., Pons Capote, O., De Tré, G. (2012). A Possibilistic Valid-Time Model. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances on Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31709-5_43

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  • DOI: https://doi.org/10.1007/978-3-642-31709-5_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31708-8

  • Online ISBN: 978-3-642-31709-5

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