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.
Identifer | oai:union.ndltd.org:uoregon.edu/oai:scholarsbank.uoregon.edu:1794/18413 |
Date | 29 September 2014 |
Creators | Sood, Kanika |
Contributors | Wilson, Christopher |
Publisher | University of Oregon |
Source Sets | University of Oregon |
Language | en_US |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Rights | All Rights Reserved. |
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