Comparison of Functional Dependency Extraction Methods and an Application of Depth First Search
| dc.contributor.advisor | Wilson, Christopher | en_US |
| dc.contributor.author | Sood, Kanika | en_US |
| dc.date.accessioned | 2014-09-29T17:51:44Z | |
| dc.date.available | 2014-09-29T17:51:44Z | |
| dc.date.issued | 2014-09-29 | |
| dc.description.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. | en_US |
| dc.identifier.uri | https://hdl.handle.net/1794/18413 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | University of Oregon | en_US |
| dc.rights | All Rights Reserved. | en_US |
| dc.subject | Databases | en_US |
| dc.subject | Extracting | en_US |
| dc.subject | Functional dependencies | en_US |
| dc.subject | KlipFind | en_US |
| dc.title | Comparison of Functional Dependency Extraction Methods and an Application of Depth First Search | en_US |
| dc.type | Electronic Thesis or Dissertation | en_US |
| thesis.degree.discipline | Department of Computer and Information Science | en_US |
| thesis.degree.grantor | University of Oregon | en_US |
| thesis.degree.level | masters | en_US |
| thesis.degree.name | M.S. | en_US |
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