Mining least relational patterns from multi relational tables
Existing mining association rules in relational tables only focus on discovering the relationship among large data items in a database. However, association rule for significant rare items that appear infrequently in a database but are highly related with other items is yet to be discovered. In this...
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| Format: | Conference or Workshop Item |
| Language: | en |
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2005
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| Online Access: | http://eprints.utm.my/7809/1/Mat_Deris_Mustafa_2005_Mining_Least_Relational_Patterns_Multi.pdf http://eprints.utm.my/7809/ http://dx.doi.org/10.1007/b11111 |
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| _version_ | 1845471885660258304 |
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| author | Selamat, Siti Hairulnita Mat Deris, Mustafa Mamat, Rabiei Bakar, Zuriana Abu |
| author_facet | Selamat, Siti Hairulnita Mat Deris, Mustafa Mamat, Rabiei Bakar, Zuriana Abu |
| author_sort | Selamat, Siti Hairulnita |
| building | UTM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Malaysia |
| content_source | UTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Existing mining association rules in relational tables only focus on discovering the relationship among large data items in a database. However, association rule for significant rare items that appear infrequently in a database but are highly related with other items is yet to be discovered. In this paper, we propose an algorithm called Extraction Least Pattern (ELP) algorithm that using a couple of predefined minimum support thresholds. Results from the implementation reveal that the algorithm is capable of mining rare item in multi relational tables. |
| format | Conference or Workshop Item |
| id | my.utm.eprints-7809 |
| institution | Universiti Teknologi Malaysia |
| language | en |
| publishDate | 2005 |
| record_format | eprints |
| spelling | my.utm.eprints-78092017-08-30T04:54:45Z http://eprints.utm.my/7809/ Mining least relational patterns from multi relational tables Selamat, Siti Hairulnita Mat Deris, Mustafa Mamat, Rabiei Bakar, Zuriana Abu QA75 Electronic computers. Computer science Existing mining association rules in relational tables only focus on discovering the relationship among large data items in a database. However, association rule for significant rare items that appear infrequently in a database but are highly related with other items is yet to be discovered. In this paper, we propose an algorithm called Extraction Least Pattern (ELP) algorithm that using a couple of predefined minimum support thresholds. Results from the implementation reveal that the algorithm is capable of mining rare item in multi relational tables. 2005 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/7809/1/Mat_Deris_Mustafa_2005_Mining_Least_Relational_Patterns_Multi.pdf Selamat, Siti Hairulnita and Mat Deris, Mustafa and Mamat, Rabiei and Bakar, Zuriana Abu (2005) Mining least relational patterns from multi relational tables. In: Lecture Notes in Computer Science(including subseries Lecture Notes in Artificial Intelligent and Lecture Notes in Bioinformatics) . http://dx.doi.org/10.1007/b11111 |
| spellingShingle | QA75 Electronic computers. Computer science Selamat, Siti Hairulnita Mat Deris, Mustafa Mamat, Rabiei Bakar, Zuriana Abu Mining least relational patterns from multi relational tables |
| title | Mining least relational patterns from multi relational tables |
| title_full | Mining least relational patterns from multi relational tables |
| title_fullStr | Mining least relational patterns from multi relational tables |
| title_full_unstemmed | Mining least relational patterns from multi relational tables |
| title_short | Mining least relational patterns from multi relational tables |
| title_sort | mining least relational patterns from multi relational tables |
| topic | QA75 Electronic computers. Computer science |
| url | http://eprints.utm.my/7809/1/Mat_Deris_Mustafa_2005_Mining_Least_Relational_Patterns_Multi.pdf http://eprints.utm.my/7809/ http://dx.doi.org/10.1007/b11111 |
| url_provider | http://eprints.utm.my/ |