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...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2005
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| Subjects: | |
| Online Access: | http://eprints.utm.my/7809/ http://eprints.utm.my/7809/1/Mat_Deris_Mustafa_2005_Mining_Least_Relational_Patterns_Multi.pdf |
| Summary: | 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. |
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