dc.contributor.author | Liu, Jixue | |
dc.contributor.author | Ye, Feiyue | |
dc.contributor.author | Li, Jiuyong | |
dc.contributor.author | Wang, Junhu | |
dc.date.accessioned | 2017-05-03T14:22:36Z | |
dc.date.available | 2017-05-03T14:22:36Z | |
dc.date.issued | 2013 | |
dc.date.modified | 2014-01-15T22:01:33Z | |
dc.identifier.issn | 0169-023X | |
dc.identifier.doi | 10.1016/j.datak.2013.01.008 | |
dc.identifier.uri | http://hdl.handle.net/10072/55652 | |
dc.description.abstract | Discovering functional dependencies (FDs) from existing databases is important to knowledge discovery, machine learning and data quality assessment. A number of algorithms have been proposed in the literature. In this paper, we review and compare these algorithms to identify their advantages and differences. We then propose a simple but time and space efficient hash-based algorithm for FD discovery. We conduct a performance comparison of three recently published algorithms and compare their performance with that of our hash-based algorithm. We show that the hash-based algorithm performs best among the four algorithms and analyze the reasons. | |
dc.description.peerreviewed | Yes | |
dc.description.publicationstatus | Yes | |
dc.language | English | |
dc.language.iso | eng | |
dc.publisher | Elsevier | |
dc.publisher.place | Netherlands | |
dc.relation.ispartofstudentpublication | N | |
dc.relation.ispartofpagefrom | 146 | |
dc.relation.ispartofpageto | 159 | |
dc.relation.ispartofjournal | Data and Knowledge Engineering | |
dc.relation.ispartofvolume | 86 | |
dc.rights.retention | Y | |
dc.subject.fieldofresearch | Data management and data science | |
dc.subject.fieldofresearch | Information systems | |
dc.subject.fieldofresearch | Database systems | |
dc.subject.fieldofresearchcode | 4605 | |
dc.subject.fieldofresearchcode | 4609 | |
dc.subject.fieldofresearchcode | 460505 | |
dc.title | On discovery of functional dependencies from data | |
dc.type | Journal article | |
dc.type.description | C1 - Articles | |
dc.type.code | C - Journal Articles | |
gro.date.issued | 2013 | |
gro.hasfulltext | No Full Text | |
gro.griffith.author | Wang, John | |