Abstract
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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Selamat, S.H., Deris, M.M., Mamat, R., Bakar, Z.A. (2005). Mining Least Relational Patterns from Multi Relational Tables. In: Li, X., Wang, S., Dong, Z.Y. (eds) Advanced Data Mining and Applications. ADMA 2005. Lecture Notes in Computer Science(), vol 3584. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527503_9
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DOI: https://doi.org/10.1007/11527503_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27894-8
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