Comparison of Functional Dependency Extraction Methods and an Application of Depth First Search
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Date
2014-09-29
Authors
Sood, Kanika
Journal Title
Journal ISSN
Volume Title
Publisher
University of Oregon
Abstract
Extracting functional dependencies from existing databases is a useful technique in relational theory, database design and data mining.
Functional dependencies are a key property of relational schema design. A functional dependency is a database constraint between two sets of attributes. In this study we present a comparative study over TANE, FUN, FD_Mine, FastFDs and Dep_Miner, and we propose a new technique, KlipFind, to extract dependencies from relations efficiently. KlipFind employs a depth-first, heuristic driven approach as a solution. Our study indicates that KlipFind is more space efficient than any of the existing solutions and highly efficient in finding keys for relations.
Description
Keywords
Databases, Extracting, Functional dependencies, KlipFind