An incremental approach to share-frequent itemsets mining

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dc.contributor.authorNawapornanany, Chayanan
dc.contributor.authorIntakosumy, Sarun
dc.contributor.authorBoonjingz, Veera
dc.date.accessioned2026-08-06T10:19:39Z
dc.date.available2026-08-06T10:19:39Z
dc.date.issued2018-04-01
dc.description.abstractThe share-frequent itemsets mining becomes an important topic in the mining of association rules because it can provide useful knowledge such as total quantity of items sold and total profit. In the past, the efficient MCShFI algorithm was successfully proposed to discover complete share-frequent itemsets on a database. When the database is updated, the algorithm can obtain current complete share-frequent itemsets by using the batch approach-mining the whole updated database. To improve mining execution time, we propose a new incremental approach to the problem with the Fast Update (FUP) concept. It obtains the current result by mining only new transactions and updating the previous existing result with this mined result.
dc.identifier.citationThai Journal of Mathematics, 16(1), 1-23, 2018
dc.identifier.issn16860209
dc.identifier.other2-s2.0-85046364692
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/8500
dc.sourceThai Journal of Mathematics
dc.subjectData mining
dc.subjectIncremental mining
dc.subjectShare-frequent itemsets mining
dc.titleAn incremental approach to share-frequent itemsets mining
dc.typeArticle

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