An Efficient Tree-Based Algorithm for Mining High Average-Utility Itemset
IEEE Access, 2019 High-utility itemset mining (HUIM), which is an extension of well-known frequent itemset mining (FIM), has become a key topic in recent years. HUIM aims to find a complete set of itemsets having high utilities in a given dataset.
Irfan Yildirim, Mete Celik
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Top ‘N’ Variant Random Forest Model for High Utility Itemsets Recommendation [PDF]
EAI Endorsed Transactions on Energy Web, 2021 High-utility based itemset mining is the advancement of recurrent pattern mining that discovers occurrence of frequent transactions from a huge database.
Pazhaniraja N +3 more
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Behavior Decoding Delineates Seizure Microfeatures and Associated Sudden Death Risks in Mouse Models of Epilepsy. [PDF]
Ann NeurolObjective Behavior and motor manifestations are distinctive yet often overlooked features of epileptic seizures. Seizures can result in transient disruptions in motor control, often organized into specific behavioral sequences that can inform seizure types, onset zones, and outcomes.
Shen Y +8 more
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High-utility Itemsets Mining Algorithm Based on Double Binary Particle Swarm Optimization [PDF]
Jisuanji gongcheng, 2018 High-utility itemset mining algorithm is an important part of association analysis.By improving the basic binary particle swarm optimization algorithm,a Double Binary Particle Swarm Optimization（DBPSO） algorithm is proposed.The minimum utility threshold ...
JIN Xiaole,LIU Xiabi,MA Xiao
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A General Method for mining high-Utility itemsets with correlated measures
Journal of Information and Telecommunication, 2021 Discovering high-utility itemsets from a transaction database is one of the important tasks in High-Utility Itemset Mining (HUIM). The discovered high-utility itemsets (HUIs) must meet a user-defined given minimum utility threshold.
Nguyen Manh Hung, Tung NT, Bay Vo
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EAHUIM: Enhanced Absolute High Utility Itemset Miner for Big Data
International Journal of Information Management Data Insights, 2022 High utility itemset mining (HUIM) is a data mining technique that identifies the itemsets with utility levels exceeding a pre-determined threshold. The factor utility is described as the combination of magnitude and element of significance for an item ...
Vandna Dahiya, Sandeep Dalal
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Efficient chain structure for high-utility sequential pattern mining [PDF]
, 2020 High-utility sequential pattern mining (HUSPM) is an emerging topic in data mining, which considers both utility and sequence factors to derive the set of high-utility sequential patterns (HUSPs) from the quantitative databases.
Djenouri, Youcef +4 more
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A review on big data based parallel and distributed approaches of pattern mining
Journal of King Saud University: Computer and Information Sciences, 2022 Pattern mining is a fundamental technique of data mining to discover interesting correlations in the data set. There are several variations of pattern mining, such as frequent itemset mining, sequence mining, and high utility itemset mining. High utility
Sunil Kumar, Krishna Kumar Mohbey
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FCHUIM: Efficient Frequent and Closed High-Utility Itemsets Mining
IEEE Access, 2020 Mining a closed high-utility itemset is a prevalent research task in analyzing transaction databases. However, numerous target itemsets are generated in the closed high-utility itemset mining task.
Tianyou Wei +5 more
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Hiding Sensitive High Utility and Frequent Itemsets Based on Constrained Intersection Lattice
Cybernetics and Information Technologies, 2022 Hiding high utility and frequent itemset is the method used to preserve sensitive knowledge from being revealed by pattern mining process. Its goal is to remove sensitive high utility and frequent itemsets from a database before sharing it for data ...
Vy Huynh Trieu +4 more
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