research-article

CPref-SQL: a query language supporting conditional preferences

Authors:

Marcos Roberto RibeiroAuthors Info & Claims

SAC '09: Proceedings of the 2009 ACM symposium on Applied Computing

Pages 1573 - 1577

https://doi.org/10.1145/1529282.1529633

Published: 08 March 2009 Publication History

Abstract

Nowadays, the need for incorporating preference querying in database technology is a very important issue in a variety of applications ranging from e-commerce to personalized search engines. A lot of recent research work has been dedicated to this topic in the artificial intelligence and database communities. Several formalisms allowing preference reasoning and specification have been proposed in the AI field. On the other hand, in the database field the interest has been focused mainly in extending standard SQL with preference facilities in order to provide personalized query answering. In this paper, we propose to build a bridge between these two approaches, by using a logic formalism originally designed to specify and reason with preference in order to extend SQL with conditional preference constructors. Such constructors allow to express a large class of preference statements with a ceteris-paribus semantics.

References

[1]

R. Agrawal, A. Borgida, and H. Jagadish. Efficient management of transitive relationships in large data and knowledge bases. In Proc. ACM SIGMOD Internacional Conference on Management of Data, pages 253--262, 1989.

Digital Library

[2]

S. Borzsonyi, D. Kossmann, and K. Stocker. The skyline operator. In Proc. 17th International Conference on Data Engineering, 2001.

Digital Library

[3]

C. Boutilier, R. Brafman, H. Hoos, and D. Poole. Cp-nets: A tool for representing and reasoning about conditional ceteris paribus preference statements. Journal of Artificial Intelligence Research, 21: 135--191, 2004.

Digital Library

[4]

R. Brafman, C. Domshlak, and S. Shimony. On graphical modeling of preference and importance. Journal of Artificial Intelligence Research, 25: 389--424, 2006.

Digital Library

[5]

C.-Y. Chan, P.-K. Eng, and K.-L. Tan. Stratified computation of skylines with partially-ordered domains. In ACM SIGMOD, 2005.

Digital Library

[6]

J. Chomicki. Preference formulas in relational queries. ACM Transactions on Database Systems, pages 427--466, 2003.

Digital Library

[7]

J. Chomicki. Semantic optimization techniques for preference queries. Information Systems, 32, 5: 670--684, 2007.

Digital Library

[8]

S. de Amo and A. Giacometti. Temporal conditional preferences over sequences of objects. In In 19th IEEE International Conference on Tools with Artificial Intelligence, Patras, Greece, pages 29--31, 2007.

Digital Library

[9]

M. Endres and W. Kießling. Transformation of tcp-net queries into preference database queries. In Proc. of the ECAI 2006 Multidisciplinary Workshop on Advances in Preference Handling, pages 23--30, 2006.

[10]

V. Hristidis, N. Koudas, and Y. Papakonstantinou. Prefer: A system for the efficient execution of multi-parametric ranked queries. In Proceedings of ACM SIGMOD, Santa Barbara, CA, USA, pages 259--270, 2001.

Digital Library

[11]

W. Kießling. Foundations of preferences in database systems. Proceedings of 28th International Conference on Very Large Data Bases, 2002, Hong Kong, China, pages 311--322, 2002.

Digital Library

[12]

W. Kießling and G. Köstler. Preference sql - design, implementation, experiences. In VLDB, pages 990--1001, 2002.

Digital Library

[13]

G. Koutrika, A. Simitsis, and Y. Ionnadis. Précis: The essence of a query answer. In Proceedings of the 22nd International Conference on Data Engineering, pages 69--78, 2006.

Digital Library

[14]

K. Stefanidis and E. Pitoura. Fast contextual preference scoring of database tuples. In Proceedings of EDBT 2008, pages 344--355.

Digital Library

[15]

K. Stefanidis, E. Pitoura, and P. Vassiliadis. A context-aware preference database system. J. Pervasive Compu. & Comm., Troubador Publishing Ltda., 1 (1), 2005.

[16]

T. Preisinger and W. Kießling. The hexagon algorithm for pareto preference queries. In 3rd Multidisciplinary Workshop on Advances in Preference Handling, VLDB 2007, 2007.

[17]

T. Preisinger, W. Kießling, and M. Endres. The bnl⁺⁺ algorithm for evaluating pareto preference queries. In 2nd Multidisciplinary Workshop on Advances in Preference Handling, ECAI 2006, 2006.

[18]

N. Wilson. Extending cp-nets with stronger conditional preference statements. In AAAI, pages 735--741, 2004.

Digital Library

Cited By

Cattelan RAraújo RFerreira HBrant-Ribeiro TDorça F(2024)Classroom eXperience: from automated multimedia capture to personalized learningMultimedia Tools and Applications10.1007/s11042-024-20238-3Online publication date: 20-Sep-2024
https://doi.org/10.1007/s11042-024-20238-3
Bianchini DDe Antonellis VGarda MMelchiori M(2020)Contextual Preferences to Personalise Semantic Data Lake ExplorationDatabase and Expert Systems Applications10.1007/978-3-030-59051-2_22(322-332)Online publication date: 13-Sep-2020
https://doi.org/10.1007/978-3-030-59051-2_22
Ribeiro MPereira FDias VOssowski S(2016)Efficient algorithms for processing preference queriesProceedings of the 31st Annual ACM Symposium on Applied Computing10.1145/2851613.2851659(972-979)Online publication date: 4-Apr-2016
https://dl.acm.org/doi/10.1145/2851613.2851659

Index Terms

CPref-SQL: a query language supporting conditional preferences

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cover image ACM Conferences

SAC '09: Proceedings of the 2009 ACM symposium on Applied Computing

March 2009

2347 pages

ISBN:9781605581668

DOI:10.1145/1529282

Conference Chairs:
Sung Y. Shin
South Dakota State University, United States
,
Sascha Ossowski
University Rey Juan Carlos, Spain

Copyright © 2009 ACM.

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Published: 08 March 2009

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SAC09: The 2009 ACM Symposium on Applied Computing

March 8, 2009 - March 12, 2008

Hawaii, Honolulu

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Cited By

Cattelan RAraújo RFerreira HBrant-Ribeiro TDorça F(2024)Classroom eXperience: from automated multimedia capture to personalized learningMultimedia Tools and Applications10.1007/s11042-024-20238-3Online publication date: 20-Sep-2024
https://doi.org/10.1007/s11042-024-20238-3
Bianchini DDe Antonellis VGarda MMelchiori M(2020)Contextual Preferences to Personalise Semantic Data Lake ExplorationDatabase and Expert Systems Applications10.1007/978-3-030-59051-2_22(322-332)Online publication date: 13-Sep-2020
https://doi.org/10.1007/978-3-030-59051-2_22
Ribeiro MPereira FDias VOssowski S(2016)Efficient algorithms for processing preference queriesProceedings of the 31st Annual ACM Symposium on Applied Computing10.1145/2851613.2851659(972-979)Online publication date: 4-Apr-2016
https://dl.acm.org/doi/10.1145/2851613.2851659
Ferreira MPonciano-Silva MTraina ATraina Cde Amo SPereira FChbeir R(2010)Integrating user preference to similarity queries over medical images datasetsProceedings of the 2010 IEEE 23rd International Symposium on Computer-Based Medical Systems10.1109/CBMS.2010.6042693(486-491)Online publication date: 12-Oct-2010
https://dl.acm.org/doi/10.1109/CBMS.2010.6042693

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