Detection of Fuzzy Association Rules by Fuzzy Transforms
We present a new method based on the use of fuzzy transforms for detecting coarse-grained association rules in the datasets. The fuzzy association rules are represented in the form of linguistic expressions and we introduce a pre-processing phase to determine the optimal fuzzy partition of the domai...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Advances in Fuzzy Systems |
| Online Access: | http://dx.doi.org/10.1155/2012/258476 |
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| _version_ | 1832562362641547264 |
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| author | Ferdinando Di Martino Salvatore Sessa |
| author_facet | Ferdinando Di Martino Salvatore Sessa |
| author_sort | Ferdinando Di Martino |
| collection | DOAJ |
| description | We present a new method based on the use of fuzzy transforms for detecting coarse-grained association rules in the datasets. The fuzzy association rules are represented in the form of linguistic expressions and we introduce a pre-processing phase to determine the optimal fuzzy partition of the domains of the quantitative attributes. In the extraction of the fuzzy association rules we use the AprioriGen algorithm and a confidence index calculated via the inverse fuzzy transform. Our method is applied to datasets of the 2001 census database of the district of Naples (Italy); the results show that the extracted fuzzy association rules provide a correct coarse-grained view of the data association rule set. |
| format | Article |
| id | doaj-art-b1b2f80ad69f488e822fce9166305e20 |
| institution | Kabale University |
| issn | 1687-7101 1687-711X |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Fuzzy Systems |
| spelling | doaj-art-b1b2f80ad69f488e822fce9166305e202025-02-03T01:22:50ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2012-01-01201210.1155/2012/258476258476Detection of Fuzzy Association Rules by Fuzzy TransformsFerdinando Di Martino0Salvatore Sessa1Dipartimento di Costruzioni e Metodi Matematici in Architettura, Università degli Studi di Napoli Federico II, Via Monteoliveto 3, 80134 Napoli, ItalyDipartimento di Costruzioni e Metodi Matematici in Architettura, Università degli Studi di Napoli Federico II, Via Monteoliveto 3, 80134 Napoli, ItalyWe present a new method based on the use of fuzzy transforms for detecting coarse-grained association rules in the datasets. The fuzzy association rules are represented in the form of linguistic expressions and we introduce a pre-processing phase to determine the optimal fuzzy partition of the domains of the quantitative attributes. In the extraction of the fuzzy association rules we use the AprioriGen algorithm and a confidence index calculated via the inverse fuzzy transform. Our method is applied to datasets of the 2001 census database of the district of Naples (Italy); the results show that the extracted fuzzy association rules provide a correct coarse-grained view of the data association rule set.http://dx.doi.org/10.1155/2012/258476 |
| spellingShingle | Ferdinando Di Martino Salvatore Sessa Detection of Fuzzy Association Rules by Fuzzy Transforms Advances in Fuzzy Systems |
| title | Detection of Fuzzy Association Rules by Fuzzy Transforms |
| title_full | Detection of Fuzzy Association Rules by Fuzzy Transforms |
| title_fullStr | Detection of Fuzzy Association Rules by Fuzzy Transforms |
| title_full_unstemmed | Detection of Fuzzy Association Rules by Fuzzy Transforms |
| title_short | Detection of Fuzzy Association Rules by Fuzzy Transforms |
| title_sort | detection of fuzzy association rules by fuzzy transforms |
| url | http://dx.doi.org/10.1155/2012/258476 |
| work_keys_str_mv | AT ferdinandodimartino detectionoffuzzyassociationrulesbyfuzzytransforms AT salvatoresessa detectionoffuzzyassociationrulesbyfuzzytransforms |