Fuzzy functional dependencies and lossless join decomposition of fuzzy relational database systems
ACM Transactions on Database Systems (TODS)
A provably efficient computational model for approximate spatiotemporal retrieval
Proceedings of the 7th ACM international symposium on Advances in geographic information systems
A relational model of data for large shared data banks
Communications of the ACM
Combining fuzzy information: an overview
ACM SIGMOD Record
Fuzzy Relational Systems: Foundations and Principles
Fuzzy Relational Systems: Foundations and Principles
Theory of Relational Databases
Theory of Relational Databases
Databases, Types and the Relational Model (3rd Edition)
Databases, Types and the Relational Model (3rd Edition)
Database in Depth: Relational Theory for Practitioners
Database in Depth: Relational Theory for Practitioners
Query systems in similarity-based databases: logical foundations, expressive power, and completeness
Proceedings of the 2010 ACM Symposium on Applied Computing
Codd's Relational Model from the Point of View of Fuzzy Logic
Journal of Logic and Computation
DASFAA'06 Proceedings of the 11th international conference on Database Systems for Advanced Applications
Two basic algorithms in concept analysis
ICFCA'10 Proceedings of the 8th international conference on Formal Concept Analysis
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We introduce a new type of dependencies for data over domains that are additionally equipped with similarity relations. The dependencies are expressed by if-then rules involving similarities of attribute values. Unlike strict equalities, similarities of attribute values make it possible to provide robust rules and concise descriptions of dependencies regarding attribute values, which are close to how a human expert perceives the data. In the paper, we define the rules, their semantics, entailment, and present an algorithm for computing nonredundant sets of rules, i.e., nonredundant sets of rules describing all if-then dependencies in given data. The algorithm represents basic method for extracting if-then rules from data in similarity-based databases. Due to the limited scope of the paper, all proofs are only skethced or omitted.