On Interactive Pattern Mining from Relational Databases

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Provided by: Springer Healthcare
Topic: Big Data
Format: PDF
In this paper, the authors present a Constraint based Querying System (ConQueSt) devised with the aim of supporting the intrinsically exploratory (i.e., human-guided, interactive, iterative) nature of pattern discovery. Following the inductive database vision, their framework provides users with an expressive constraint based query language which allows the discovery process to be effectively driven toward potentially interesting patterns. Such constraints are also exploited to reduce the cost of pattern mining computation. They implemented a comprehensive mining system that can access real world relational databases from which extract data.
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