CoBase: a scalable and extensible cooperative information system
Journal of Intelligent Information Systems - Special issue on intelligent integration of information
Accurate estimation of the number of tuples satisfying a condition
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Cooperative Answering through Controlled Query Relaxation
IEEE Expert: Intelligent Systems and Their Applications
On the Weakening of Fuzzy Relational Queries
ISMIS '94 Proceedings of the 8th International Symposium on Methodologies for Intelligent Systems
Flexibility and fuzzy case-based evaluation in querying: an illustration in an experimental setting
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Failing queries in distributed autonomous information system
ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
Qualitative reasoning based on fuzzy relative orders of magnitude
IEEE Transactions on Fuzzy Systems
Empty versus overabundant answers to flexible relational queries
Fuzzy Sets and Systems
Incremental controlled relaxation of failing flexible queries
Journal of Intelligent Information Systems
Cooperative answering to flexible queries via a tolerance relation
ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
Relaxation paradigm in a flexible querying context
FQAS'06 Proceedings of the 7th international conference on Flexible Query Answering Systems
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
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In this paper, we present a cooperative approach for avoiding empty answers to fuzzy relational queries. We propose a relaxation mechanism generating more tolerant queries. This mechanism rests on a transformation that consists in applying a tolerance relation to fuzzy predicates contained in the query. A particular tolerance relation, which can be conveniently modeled in terms of a parameterized proximity relation, is discussed. The modified fuzzy predicate is obtained by a simple arithmetic operation on fuzzy numbers. We show that this proximity relation can be defined in a relative or in an absolute way. In each case, the main features of the resulting weakening mechanism are investigated. We also show that the limits of the transformation, that guarantee that the weakened query is not semantically too far from the original one, can be handled in a non-empirical rigorous way without requiring any additional information from the user. Lastly, to illustrate our proposal an example is considered.