Abstract
We deal with algorithmic aspects and implementation issues of query execution in relational similarity-based databases. We are concerned with a generalized relational model of data in which queries can be matched to degrees taken from scales represented by complete residuated lattices. The main contribution of this paper are optimization techniques for efficient evaluation of queries involving similarity-based restrictions. In addition, we present experimental evaluation of the proposed techniques showing their efficiency compared to naive approaches.
Keywords
P. Krajca is supported by grant no. P103/11/1456 of the Czech Science Foundation; V. Vychodil is supported by project reg. no. CZ.1.07/2.3.00/20.0059 of the European Social Fund in the Czech Republic.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Belohlavek, R.: Fuzzy Relational Systems: Foundations and Principles. Kluwer Academic Publishers, Norwell (2002)
Belohlavek, R., Opichal, S., Vychodil, V.: Relational algebra for ranked tables with similarities: Properties and implementation. In: Berthold, M.R., Shawe-Taylor, J., Lavrac, N. (eds.) IDA 2007. LNCS, vol. 4723, pp. 140–151. Springer, Heidelberg (2007)
Bělohlávek, R., Vychodil, V.: Data tables with similarity relations: Functional dependencies, complete rules and non-redundant bases. In: Li Lee, M., Tan, K.-L., Wuwongse, V. (eds.) DASFAA 2006. LNCS, vol. 3882, pp. 644–658. Springer, Heidelberg (2006)
Belohlavek, R., Vychodil, V.: Query systems in similarity-based databases: logical foundations, expressive power, and completeness. In: ACM Symposium on Applied Computing (SAC), pp. 1648–1655. ACM (2010)
Buckles, B.P., Petry, F.E.: A fuzzy representation of data for relational databases. Fuzzy Sets and Systems 7(3), 213–226 (1982)
Cavallo, R., Pittarelli, M.: The theory of probabilistic databases. In: Proceedings of the 13th International Conference on Very Large Data Bases, VLDB 1987, pp. 71–81. Morgan Kaufmann Publishers Inc., San Francisco (1987)
Cintula, P., Hájek, P.: Triangular norm based predicate fuzzy logics. Fuzzy Sets and Systems 161, 311–346 (2010)
Codd, E.F.: A relational model of data for large shared data banks. Communications of the ACM 26, 64–69 (1983)
Dalvi, N., Ré, C., Suciu, D.: Probabilistic databases: diamonds in the dirt. Commun. ACM 52, 86–94 (2009)
Dalvi, N., Suciu, D.: Efficient query evaluation on probabilistic databases. The VLDB Journal 16, 523–544 (2007)
Dalvi, N., Suciu, D.: Management of probabilistic data: foundations and challenges. In: Proc. ACM PODS 2007, pp. 1–12. ACM, New York (2007)
Date, C.J., Darwen, H.: Databases, Types, and The Relational Model: The Third Manifesto, 3rd edn. Addison-Wesley (2006)
Date, C.J.: Database in Depth: Relational Theory for Practitioners: The Relational Model for Practitioners, 1st edn. O’Reilly Media (2005)
Esteva, F., Godo, L.: Monoidal t-norm based logic: towards a logic for left-continuous t-norms. Fuzzy Sets and Systems 124(3), 271–288 (2001)
Fagin, R.: Combining fuzzy information from multiple systems. J. Comput. Syst. Sci. 58(1), 83–99 (1999)
Goguen, J.A.: The logic of inexact concepts. Synthese 19, 325–373 (1979)
Gottwald, S.: Mathematical fuzzy logics. Bull. Symb. Logic 14(2), 210–239 (2008)
Gupta, R., Sarawagi, S.: Creating probabilistic databases from information extraction models. In: Proceedings of the 32nd International Conference on Very large Data Bases, VLDB 2006, pp. 965–976. VLDB Endowment (2006)
Hájek, P.: Metamathematics of Fuzzy Logic. Kluwer Academic Publishers, Dordrecht (1998)
Ilyas, I.F., Beskales, G., Soliman, M.A.: A survey of top-k query processing techniques in relational database systems. ACM Comp. Surv. 40(4), 11:1–11:58 (2008)
Klement, E.P., Mesiar, R., Pap, E.: Triangular Norms, 1st edn. Springer (2000)
Krajca, P., Vychodil, V.: Foundations of relational similarity-based query language RESIQL. In: Proc. 2013 IEEE Symposium on Foundations of Computational Intelligence (FOCI), pp. 15–23. IEEE (2013)
Li, C., Chang, K.C.C., Ilyas, I.F., Song, S.: Ranksql: query algebra and optimization for relational top-k queries. In: Proc. 2005 ACM SIGMOD, pp. 131–142 (2005)
Maier, D.: The Theory of Relational Databases. Computer Science Press (1983)
Prade, H., Testemale, C.: Generalizing database relational algebra for the treatment of incomplete or uncertain information and vague queries. Information Sciences 34(2), 115–143 (1984)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Krajca, P., Vychodil, V. (2013). Query Optimization Strategies in Similarity-Based Databases. In: Torra, V., Narukawa, Y., Navarro-Arribas, G., Megías, D. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2013. Lecture Notes in Computer Science(), vol 8234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41550-0_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-41550-0_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41549-4
Online ISBN: 978-3-642-41550-0
eBook Packages: Computer ScienceComputer Science (R0)