Principles of database and knowledge-base systems, Vol. I
Principles of database and knowledge-base systems, Vol. I
Fast discovery of association rules
Advances in knowledge discovery and data mining
An Extension to SQL for Mining Association Rules
Data Mining and Knowledge Discovery
Composition of Mining Contexts for Efficient Extraction of Association Rules
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
Relational Association Rules: Getting WARMeR
Proceedings of the ESF Exploratory Workshop on Pattern Detection and Discovery
Mining Association Rules in Multiple Relations
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
Data Mining and Knowledge Discovery
Mining tree queries in a graph
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Towards mining frequent queries in star schemes
KDID'05 Proceedings of the 4th international conference on Knowledge Discovery in Inductive Databases
Mining frequent conjunctive queries in star schemas
IDEAS '09 Proceedings of the 2009 International Database Engineering & Applications Symposium
Towards a novel approach to multimedia data mixed fragmentation
Proceedings of the International Conference on Management of Emergent Digital EcoSystems
Computing Supports of Conjunctive Queries on Relational Tables with Functional Dependencies
Fundamenta Informaticae
Discovery and application of functional dependencies in conjunctive query mining
DaWaK'10 Proceedings of the 12th international conference on Data warehousing and knowledge discovery
An efficient computation of frequent queries in a star schema
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
Mining frequent disjunctive selection queries
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part II
Rewriting aggregate queries using functional dependencies
Proceedings of the International Conference on Management of Emergent Digital EcoSystems
Mining frequent conjunctive queries using functional and inclusion dependencies
The VLDB Journal — The International Journal on Very Large Data Bases
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In this paper we study the problem of mining all frequent queries in a given database table, a problem known to be intractable even for conjunctive queries. We restrict our attention to projection-selection queries, and we assume that the table to be mined satisfies a set of functional dependencies. Under these assumptions we define a pre-ordering &cupre; over queries and we show the following: (a) the support measure is anti-monotonic (with respect to &cupre;), and (b) if we define q &cupre; q' iff q &cupre; q' and q' &cupre; q then all queries of an equivalence class have the same support. With these results at hand, we further restrict our attention to star schemas of data warehouses. In those schemas, the set of functional dependencies satisfies an important property, namely, the union of keys of all dimension tables is a key for the fact table. The main contribution of this paper is the proposal of a level-wise algorithm for mining all frequent projection-selection queries in a data warehouse over a star schema. Moreover, we show that, in the case of a star schema, the complexity in the number of scans of our algorithm is similar to that of the well known Apriori algorithm, i.e., linear with respect to the number of attributes.