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ACM Transactions on Information Systems (TOIS)
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Theoretical Computer Science
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SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
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Applied Intelligence
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FQAS '02 Proceedings of the 5th International Conference on Flexible Query Answering Systems
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VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
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ACM Transactions on Database Systems (TODS)
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Annals of Mathematics and Artificial Intelligence
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VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
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AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Journal of Artificial Intelligence Research
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
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ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
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FQAS '09 Proceedings of the 8th International Conference on Flexible Query Answering Systems
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International Journal of Approximate Reasoning
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Artificial Intelligence
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ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
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ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
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ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
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ACM SIGAPP Applied Computing Review
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Journal of Intelligent Information Systems
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FQAS'11 Proceedings of the 9th international conference on Flexible Query Answering Systems
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FQAS'11 Proceedings of the 9th international conference on Flexible Query Answering Systems
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ADBIS'12 Proceedings of the 16th East European conference on Advances in Databases and Information Systems
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The paper presents a new approach to database preferences queries, where preferences are represented in a possibilistic logic manner, using symbolic weights. The symbolic weights may be processed without assessing their precise value, which leaves the freedom for the user to not specify any priority among the preferences. The user may also enforce a (partial) ordering between them, if necessary. The approach can be related to the processing of fuzzy queries whose components are conditionally weighted in terms of importance. Here, importance levels are symbolically processed, and refinements of both Pareto ordering and minimum ordering are used. The representational power of the proposed setting is stressed, while the approach is compared with database Best operator-like methods and with the CP-net approach developed in artificial intelligence. The paper also provides a structured and rather broad overview of the different lines of research in the literature dealing with the handling of preferences in database queries.