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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