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Using SAT and SQL for Pattern Mining in Relational Databases

In this paper, we present an ongoing work bridging the gap between pattern mining, SQL and SAT for a particular class of patterns. We extend the work presented in [2] that proposes a logical query language for rule patterns satisfying Armstrong’s axioms. Our contributions are the following: firstly, we allow a large part of the relational tuple calculus (SQL) to be used in the specification of queries. Secondly, we propose a boolean encoding of the query that can be used to compute answers even in the case of non Armstrongcompliant queries. Some experiments have been performed on top of Derby (embedded Java DBMS) and a modified version of MiniSat to show the feasibility of the approach.