Abstract
Information often comes from multiple sources that may be conflicting. This makes uncertain the answers of a query to a set of sources. Possibility theory-based approaches to the handling of uncertainty in databases have been proposed and developed for a long time, in the case of a unique source of information. A multiple source counterpart of possibility theory has been recently proposed. Possibility and necessity set functions are then valued in terms of (possibly fuzzy) subsets of sources. Uncertainty may be assessed here either in terms of global reliability levels of sources or of tuples inside a source. When each source contains precise attribute values, each tuple is associated with the subset of sources that supports it as being an answer to a considered query, and with the subset of sources according to which the tuple is not an answer. In fact, these subsets of sources are fuzzy as they reflect the reliability levels. The benefit of the approach is to rank-order the answers to a query on a qualitative basis, in terms of subsets of sources and reliability levels.
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References
Agarwal, S., Keller, A.M., Wiederhold, G., Saraswat, K.: Flexible relation: An approach for integrating data from multiple, possibly inconsistent databases. In: Yu, P.S., Chen, A.L.P. (eds.) ICDE, pp. 495–504. IEEE Computer Society (1995)
Assaghir, Z., Napoli, A., Kaytoue, M., Dubois, D., Prade, H.: Numerical information fusion: Lattice of answers with supporting arguments. In: ICTAI, pp. 621–628. IEEE (2011)
Belhadi, A., Dubois, D., Khellaf-Haned, F., Prade, H.: Multiple agent possibilistic logic. Journal of Applied Non-Classical Logics 23(4), 299–320 (2013)
Bertossi, L.E.: Consistent query answering in databases. SIGMOD Record 35(2), 68–76 (2006)
Bienvenu, M., Rosati, R.: Tractable approximations of consistent query answering for robust ontology-based data access. In: Rossi, F. (ed.) IJCAI. IJCAI/AAAI (2013)
Bloch, I., Hunter, A., Appriou, A., Ayoun, A., Benferhat, S., Besnard, P., Cholvy, L., Cooke, R.M., Cuppens, F., Dubois, D., Fargier, H., Grabisch, M., Kruse, R., Lang, J., Moral, S., Prade, H., Saffiotti, A., Smets, P., Sossai, C.: Fusion: General concepts and characteristics. Int. J. Intell. Syst. 16(10), 1107–1134 (2001)
Bosc, P., Pivert, O.: About projection-selection-join queries addressed to possibilistic relational databases. IEEE T. Fuzzy Systems 13(1), 124–139 (2005)
Bosc, P., Pivert, O., Prade, H.: A model based on possibilistic certainty levels for incomplete databases. In: Godo, L., Pugliese, A. (eds.) SUM 2009. LNCS, vol. 5785, pp. 80–94. Springer, Heidelberg (2009)
Deagustini, C.A.D., Fulladoza Dalibón, S.E., Gottifredi, S., Falappa, M.A., Simari, G.R.: Consistent query answering using relational databases through argumentation. In: Liddle, S.W., Schewe, K.-D., Tjoa, A.M., Zhou, X. (eds.) DEXA 2012, Part II. LNCS, vol. 7447, pp. 1–15. Springer, Heidelberg (2012)
Decker, H., Martinenghi, D.: Avenues to flexible data integrity checking. In: DEXA Workshops, pp. 425–429. IEEE Computer Society (2006)
Dubois, D., Lang, J., Prade, H.: Possibilistic logic. In: Gabbay, D., Hogger, C., Robinson, J. (eds.) Handbook of Logic in Artificial Intelligence and Logic Programming, vol. 3. Oxford University Press, Oxford (1994)
Dubois, D., Prade, H.: Possibility theory and data fusion in poorly informed environments. Control Eng. Practice 2, 811–823 (1994)
Genesereth, M.R., Keller, A.M., Duschka, O.M.: Infomaster: An information integration system. In: Peckham, J. (ed.) SIGMOD Conference, pp. 539–542. ACM Press (1997)
Motro, A., Anokhin, P.: Fusionplex: resolution of data inconsistencies in the integration of heterogeneous information sources. Information Fusion 7(2), 176–196 (2006)
Pivert, O., Prade, H.: Detecting suspect answers in the presence of inconsistent information. In: Lukasiewicz, T., Sali, A. (eds.) FoIKS 2012. LNCS, vol. 7153, pp. 278–297. Springer, Heidelberg (2012)
Tseng, F.S.C., Chen, A.L.P., Yang, W.P.: A probabilistic approach to query processing in heterogeneous database systems. In: Yu, P.S. (ed.) RIDE-TQP, pp. 176–183. IEEE Computer Society (1992)
Yu, J., Wessels, D., Li, Y.Q.: Fuzzy algorithm for selection of reliable information from a collection of different data sources. In: Klein, B.D., Rossin, D.F. (eds.) IQ, pp. 76–82. MIT (2000)
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Pivert, O., Prade, H. (2014). Querying Uncertain Multiple Sources. In: Straccia, U., Calì, A. (eds) Scalable Uncertainty Management. SUM 2014. Lecture Notes in Computer Science(), vol 8720. Springer, Cham. https://doi.org/10.1007/978-3-319-11508-5_24
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DOI: https://doi.org/10.1007/978-3-319-11508-5_24
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