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IEEE Access, 2018 High average-utility itemsets mining (HAUIM) is an emerging topic in data mining. Compared to traditional high utility itemset mining, HAUIM more fairly measures the utility of itemsets by considering their lengths (number of items).
Jerry Chun-Wei Lin +2 more
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JUTI: Jurnal Ilmiah Teknologi InformasiThis research proposes the optimization of the Frequent Closed High-Utility Itemset Mining (FCHUIM) algorithm for retail transaction datasets using heuristic-based pruning techniques, Observed Support Ratio (OSR), Observed Weighted Lift (OWL), and ...
Kinana Syah Sulanjari, Chastine Fatichah
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AN EFFICIENT ALGORITHM FOR MINING HIGH UTILITY ITEMSETS
Tạp chí Khoa họcHigh utility itemsets (HUIs) mining is the finding of itemsets that satisfy a user-defined minimum utility threshold. Many successful studies in this field have been carried out, however they are all reliant on Tidset techniques, which records the ...
Nguyen Thi Thanh Thuy*, Nguyen Van Le, Manh Thien Ly
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RECENT ADVANCES IN UTILITY-DRIVEN PATTERN MINING [PDF]
International Journal of Intelligent Computing and Information SciencesKnowledge discovery is a key part of Artificial Intelligence that focuses on finding valuable, hidden patterns and insights in large amounts of complex data.
Mohamed Ashraf +3 more
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A SURVEY ON ITEMSET MINING FOR LARGE TRANSACTION DATABASE
, 2016 Mining itemsets from the databases is an important data mining task.Frequent itemset mining refers to the mining of set of items occur frequently in the database.Utility itemset mining refers to the discovery of items with high utilities.
Ancy Jose*, Dr. John T Abraham
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Comparison and Analysis of Three Measures for High Average-Utility Itemset Mining
MathematicsHigh average-utility itemset mining is a significant research direction in data mining. The traditional average-utility (AU) measure employs itemset length as the normalization benchmark, which mitigates the bias toward long itemsets; however, it does ...
Yumei Li +6 more
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Mining frequent itemsets a perspective from operations research [PDF]
Many papers on frequent itemsets have been published. Besides somecontests in this field were held. In the majority of the papers the focus ison speed. Ad hoc algorithms and datastructures were introduced.
Kosters, W.A., Pijls, W.H.L.M.
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Pencarian High Utility Itemset pada Dataset YooChoose Buys [PDF]
Abstrak. Perkembangan e-commerce yang pesat, membuat strategi penjualan harus dioptimalkan untuk meningkatkan keuntungan bisnis. Dalam upaya untuk meningkatkan keuntungan, penting untuk mengidentifikasi pola pembelian pelanggan yang dapat memberikan ...
Gunawan, Ridowati, Nugroho, Rangga
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, 2017 Data Mining is an activity that extracts some new useful information contained in large databases. Traditional data mining methodologies focused largely on detecting the statistical correlations between the items that are more frequent in the transaction
Ganesan, M, Shankar, S
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TKU-PSO: An Efficient Particle Swarm Optimization Model for Top-K High-Utility Itemset Mining.
International Journal of Interactive Multimedia and Artificial IntelligenceTop-k high-utility itemset mining (top- HUIM) is a data mining procedure used to identify the most valuable patterns within transactional data. Although many algorithms are proposed for this purpose, they require substantial execution times when the ...
Simen Carstensen, Jerry Chun Wei Lin
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