Indiana University Bloomington

Luddy School of Informatics, Computing, and Engineering

Technical Report TR678:
Modularizing Data Mining: A Case Study Framework

Jeremy T. Engle, Edward L. Robertson
(Jul 2009), Pages 7 pages
[To be submitted]
This paper presents the fundamental concepts underpinning MoLS, a framework for exploring and applying many variations of algorithms for one data mining problem: mining a database relation for Approximate Functional Dependencies (AFDs). An engineering approach to AFD mining suggests a framework which can be customized with plug-ins, yielding targetability and improved performance. This paper organizes familiar approaches for navigating a search spaces and introduces a new concepts to define and utilize variations of those spaces.

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