Abstract
In this paper, we define an approach to database preference queries based on the fusion of local orders. The situation considered is that of queries involving incommensurable partial preferences, possibly associated with scoring functions. The basic principle is to rank the tuples according to each partial preference, then to merge the local orders obtained, using a linear function for aggregating the local scores attached to the tuples. Basically, a local score expresses the extent to which a tuple is strictly better than many others and not strictly worse than many others with respect to the partial preference attached to a given attribute. This model refines Pareto order for queries of the Skyline type.
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References
Hadjali, A., Kaci, S., Prade, H.: Database preferences queries – a possibilistic logic approach with symbolic priorities. In: Hartmann, S., Kern-Isberner, G. (eds.) FoIKS 2008. LNCS, vol. 4932, pp. 291–310. Springer, Heidelberg (2008)
Bruno, N., Chaudhuri, S., Gravano, L.: Top-k selection queries over relational databases: mapping strategies and performance evaluation. ACM Transactions on Database Systems 27(2), 153–187 (2002)
Bosc, P., Pivert, O.: SQLf: a relational database language for fuzzy querying. IEEE Trans. on Fuzzy Systems 3, 1–17 (1995)
Agrawal, R., Wimmers, E.L.: A framework for expressing and combining preferences. In: Proc. of SIGMOD 2000, pp. 297–306 (2000)
Fishburn, P.C.: Preferences structures and their numerical representation. Theoretical Computer Science 217, 359–383 (1999)
Chomicki, J.: Preference formulas in relational queries. ACM Transactions on Database Systems 28(4), 427–466 (2003)
Kießling, W., Köstler, G.: Preference SQL — design, implementation, experiences. In: Bressan, S., Chaudhri, A.B., Li Lee, M., Yu, J.X., Lacroix, Z. (eds.) CAiSE 2002 and VLDB 2002. LNCS, vol. 2590, pp. 990–1001. Springer, Heidelberg (2003)
Bőrzsőnyi, S., Kossmann, D., Stocker, K.: The skyline operator. In: Proc. of the 17th IEEE Inter. Conf. on Data Engineering, pp. 421–430 (2001)
Bosc, P., Pivert, O., Smits, G.: A model based on outranking for database preference queries. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds.) IPMU 2010. Communications in Computer and Information Science, vol. 81, pp. 95–104. Springer, Heidelberg (2010)
Roy, B.: The outranking approach and the foundations of ELECTRE methods. Theory and Decision 31, 49–73 (1991)
Bosc, P., Pivert, O., Smits, G.: A database preference query model based on a fuzzy outranking relation. In: Proc. of the 19th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2010), Barcelona, Spain (2010)
Godfrey, P., Shipley, R., Gryz, J.: Maximal vector computation in large data sets. In: Proc. of VLDB 2005, pp. 229–240 (2005)
Bartolini, I., Ciaccia, P., Patella, M.: Efficient sort-based skyline evaluation. ACM Trans. Database Syst. 33(4), 1–49 (2008)
Lin, X., Yuan, Y., Zhang, Q., Zhang, Y.: Selecting stars: the k most representative skyline operator. In: Proc. of the ICDE 2007, pp. 86–95 (2007)
Chan, C.Y., Jagadish, H.V., Tan, K.L., Tung, A.K.H., Zhang, Z.: Finding k-dominant skylines in high dimensional space. In: Proc. of SIGMOD 2006, pp. 503–514 (2006)
Chan, C.Y., Jagadish, H.V., Tan, K.L., Tung, A.K.H., Zhang, Z.: On high dimensional skylines. In: Ioannidis, Y., Scholl, M.H., Schmidt, J.W., Matthes, F., Hatzopoulos, M., Böhm, K., Kemper, A., Grust, T., Böhm, C. (eds.) EDBT 2006. LNCS, vol. 3896, pp. 478–495. Springer, Heidelberg (2006)
Hadjali, A., Pivert, O., Prade, H.: On different types of fuzzy skylines. In: Proc. of the 19th International Symposium on Methodologies for Intelligent Systems (ISMIS 2011), Warsaw, Poland (2011)
Rademaker, M., De Baets, B.: A threshold for majority in the context of aggregating partial order relations. In: Proc. of the 19th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2010), Barcelona, Spain, pp. 490–493 (2010)
Bordogna, G., Pasi, G.: A model for a soft fusion of information accesses on the web. Fuzzy Sets and Systems 148(1), 105–118 (2004)
Grzegorzewski, P.: Kendall’s correlation coefficient for vague preferences. Soft Comput. 13(11), 1055–1061 (2009)
Bosc, P., Pivert, O.: On a fuzzy group-by clause in SQLf. In: Proc. of the 19th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2010), Barcelona, Spain, pp. 2409–2414 (2010)
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Bosc, P., Pivert, O., Smits, G. (2011). A Preference Query Model Based on a Fusion of Local Orders. In: Liu, W. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2011. Lecture Notes in Computer Science(), vol 6717. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22152-1_61
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DOI: https://doi.org/10.1007/978-3-642-22152-1_61
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