The partition model: a deductive database model
ACM Transactions on Database Systems (TODS)
Efficient mining of association rules using closed itemset lattices
Information Systems
On Finding the Maxima of a Set of Vectors
Journal of the ACM (JACM)
On the Structure of Armstrong Relations for Functional Dependencies
Journal of the ACM (JACM)
Generating non-redundant association rules
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
Functional and embedded dependency inference: a data mining point of view
Information Systems - Special issue on Databases: creation, management and utilization
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Data Mining and Knowledge Discovery
Computing iceberg concept lattices with TITANIC
Data & Knowledge Engineering
Efficient Discovery of Functional Dependencies and Armstrong Relations
EDBT '00 Proceedings of the 7th International Conference on Extending Database Technology: Advances in Database Technology
Proceedings of the 17th International Conference on Data Engineering
Computing Full and Iceberg Datacubes Using Partitions
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
Mining Minimal Non-redundant Association Rules Using Frequent Closed Itemsets
CL '00 Proceedings of the First International Conference on Computational Logic
Extracting semantics from data cubes using cube transversals and closures
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Generating a Condensed Representation for Association Rules
Journal of Intelligent Information Systems
Efficient computation of the skyline cube
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Catching the best views of skyline: a semantic approach based on decisive subspaces
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Towards multidimensional subspace skyline analysis
ACM Transactions on Database Systems (TODS)
Quotient cube: how to summarize the semantics of a data cube
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
ROLAP implementations of the data cube
ACM Computing Surveys (CSUR)
Emerging Cubes: Borders, size estimations and lossless reductions
Information Systems
Reduced representations of Emerging Cubes for OLAP database mining
International Journal of Business Intelligence and Data Mining
Conditional functional dependencies: an FCA point of view
ICFCA'10 Proceedings of the 8th international conference on Formal Concept Analysis
ICFCA'10 Proceedings of the 8th international conference on Formal Concept Analysis
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In this paper we propose the characterization of two new structures, the Agree Concept Lattice and the Quotient Agree Lattice of a database relation. Both of them are of great interest for multidimensional database analysis. They provide a formal framework which makes it possible to improve computation time, reduce representation and easily navigate through the Hasse diagram. These structures are generic, apply to various database analysis problems and combine formal concept analysis and database theory. They make use of the concepts of agree set and database partition. Agree set and partition are associated to define the Agree Concept of a database relation. The set of all the Agree Concepts is organized within the Agree Concept Lattice. The Quotient Agree Lattice is along the lines of both the TITANIC framework and the quotient cube. We also briefly present three application fields of the proposed structures. The first two ones are classical since they concern on the one hand the discovery of functional and approximate dependencies for database design and tuning and on the other hand the data cube computation and representation. The latter field has been recently investigated. The underlying issue is to retrieve the most relevant objects according to the user expectations: the SKYLINE. The multidimensional generalization of the SKYLINE has been proposed through the SKYCUBE. The proposed structures smartly solve the problem of partial materialization of SKYCUBE with reconstruction guarantee.