Abstract
The problem of mining all frequent queries in a database is intractable, even if we consider conjunctive queries only. In this paper, we study this problem under reasonable restrictions on the database, namely: (i) the database scheme is a star scheme; (ii) the data in the database satisfies a set of functional dependencies and a set of referential constraints.
We note that star schemes are considered to be the most appropriate schemes for data warehouses, while functional dependencies and referential constraints are the most common constraints that one encounters in real databases. Our approach is based on the weak instance semantics of databases and considers the class of selection-projection queries over weak instances. In such a context, we show that frequent queries can be mined using level-wise algorithms such as Apriori.
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Jen, TY., Laurent, D., Spyratos, N., Sy, O. (2006). Towards Mining Frequent Queries in Star Schemes. In: Bonchi, F., Boulicaut, JF. (eds) Knowledge Discovery in Inductive Databases. KDID 2005. Lecture Notes in Computer Science, vol 3933. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11733492_7
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DOI: https://doi.org/10.1007/11733492_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33292-3
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