Finding Exception For Association Rules Via SQL Queries
Finding association rules is mainly based on generating larger and larger frequent set candidates, starting from frequent attributes in the database. The frequent sets can be organised as a part of a lattice of concepts according to the Formal Concept Analysis approach. Since the lattice constructio...
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| Format: | Article |
| Language: | English |
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Universitatea Dunarea de Jos
2000-12-01
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| Series: | Analele Universităţii "Dunărea de Jos" Galaţi: Fascicula III, Electrotehnică, Electronică, Automatică, Informatică |
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| Online Access: | http://www.ann.ugal.ro/eeai/archives/lb.pdf |
| _version_ | 1819041391731277824 |
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| author | Luminita DUMITRIU |
| author_facet | Luminita DUMITRIU |
| author_sort | Luminita DUMITRIU |
| collection | DOAJ |
| description | Finding association rules is mainly based on generating larger and larger frequent set candidates, starting from frequent attributes in the database. The frequent sets can be organised as a part of a lattice of concepts according to the Formal Concept Analysis approach. Since the lattice construction is database contents-dependent, the pseudo-intents (see Formal Concept Analysis) are avoided. Association rules between concept intents (closed sets) A=>B are partial implication rules, meaning that there is some data supporting A and (not B); fully explaining the data requires finding exceptions for the association rules. The approach applies to Oracle databases, via SQL queries. |
| first_indexed | 2024-12-21T09:24:15Z |
| format | Article |
| id | doaj.art-4b4b8acbc98e4777a0de65fc3442446b |
| institution | Directory Open Access Journal |
| issn | 1221-454X |
| language | English |
| last_indexed | 2024-12-21T09:24:15Z |
| publishDate | 2000-12-01 |
| publisher | Universitatea Dunarea de Jos |
| record_format | Article |
| series | Analele Universităţii "Dunărea de Jos" Galaţi: Fascicula III, Electrotehnică, Electronică, Automatică, Informatică |
| spelling | doaj.art-4b4b8acbc98e4777a0de65fc3442446b2022-12-21T19:08:57ZengUniversitatea Dunarea de JosAnalele Universităţii "Dunărea de Jos" Galaţi: Fascicula III, Electrotehnică, Electronică, Automatică, Informatică1221-454X2000-12-01200016570Finding Exception For Association Rules Via SQL QueriesLuminita DUMITRIUFinding association rules is mainly based on generating larger and larger frequent set candidates, starting from frequent attributes in the database. The frequent sets can be organised as a part of a lattice of concepts according to the Formal Concept Analysis approach. Since the lattice construction is database contents-dependent, the pseudo-intents (see Formal Concept Analysis) are avoided. Association rules between concept intents (closed sets) A=>B are partial implication rules, meaning that there is some data supporting A and (not B); fully explaining the data requires finding exceptions for the association rules. The approach applies to Oracle databases, via SQL queries.http://www.ann.ugal.ro/eeai/archives/lb.pdfdata miningassociation rulesexceptionsSQL |
| spellingShingle | Luminita DUMITRIU Finding Exception For Association Rules Via SQL Queries Analele Universităţii "Dunărea de Jos" Galaţi: Fascicula III, Electrotehnică, Electronică, Automatică, Informatică data mining association rules exceptions SQL |
| title | Finding Exception For Association Rules Via SQL Queries |
| title_full | Finding Exception For Association Rules Via SQL Queries |
| title_fullStr | Finding Exception For Association Rules Via SQL Queries |
| title_full_unstemmed | Finding Exception For Association Rules Via SQL Queries |
| title_short | Finding Exception For Association Rules Via SQL Queries |
| title_sort | finding exception for association rules via sql queries |
| topic | data mining association rules exceptions SQL |
| url | http://www.ann.ugal.ro/eeai/archives/lb.pdf |
| work_keys_str_mv | AT luminitadumitriu findingexceptionforassociationrulesviasqlqueries |