Results 31 to 40 of about 311 (178)
Ignoring Internal Utilities in High-Utility Itemset Mining
Symmetry, 2022 High-utility itemset mining discovers a set of items that are sold together and have utility values higher than a given minimum utility threshold. The utilities of these itemsets are calculated by considering their internal and external utility values, which correspond, respectively, to the quantity sold of each item in each transaction and profit ...
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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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Pruning Strategy on Adaptive Rule Model by Sorting Utility Items
IEEE Access, 2022 The adaptive Rule Model is an association rule development that formulates a minimum threshold value according to the data characteristics. The formulation process is based on item frequency and utility for other considerations, which requires high ...
Erna Hikmawati +2 more
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Closed High Utility Pattern Mining over Data Stream Based on Projection in the Window
Taiyuan Ligong Daxue xuebao, 2022 A fast and effective algorithm EFIM_Closed_DS was proposed to mine closed and high utility itemsets in the data stream environment. The algorithm is based on the projection technology in the window, and the database projection technology and transaction ...
Muhang LI +4 more
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An Efficient Approach for Mining High Average-Utility Itemsets in Incremental Database
Engineering ProceedingsTraditional high-utility itemset (HUI) mining methods tend to overestimate utility for long itemsets, leading to biased results. High average-utility itemset (HAUI) mining addresses this problem by normalizing utility with itemset length.
Ye-In Chang +2 more
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Improved Genetic Algorithm for High-Utility Itemset Mining
IEEE Access, 2019 High-utility itemset mining (HUIM) is an important research topic in the data mining field. Typically, traditional HUIM algorithms must handle the exponential problem of huge search space when the database size or number of distinct items is very large ...
Qiang Zhang +3 more
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Data-Driven Materials Research and Development for Functional Coatings. [PDF]
Adv Sci (Weinh)Functional coatings play a vital role in various industries for their protective and functional properties. However, its design often involves time‐consuming experimentation with multiple materials and processing parameters. To overcome these limitations, data‐driven approaches are gaining traction in materials science. This review provides an overview
Xu K +8 more
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Parallel Mining Algorithm for the Enumeration Space of Closed High Utility Itemsets
Journal of Harbin University of Science and TechnologyTo address the issues of result redundancy and time overhead in high-dimensional data environments, a closed high utility itemset mining algorithm, SpCHUIM (Closed High Utility Itemsets Mining on Spark), is proposed.
LI Chengyan, SUN Anqi, LIU Songlin
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An Evolutionary Algorithm to Mine High-Utility Itemsets
Advances in Electrical and Electronic Engineering, 2015 High-utility itemset mining (HUIM) is a critical issue in recent years since it can be used to reveal the profitable products by considering both the quantity and profit factors instead of frequent itemset mining (FIM) of association rules (ARs). In this
Jerry Chun-Wei Lin +5 more
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Proof Learning in PVS With Utility Pattern Mining
IEEE Access, 2020 Interactive theorem provers (ITPs) are software tools that allow human users to write and verify formal proofs. In recent years, an emerging research area in ITPs is proof mining, which consists of identifying interesting proof patterns that can be used ...
M. Saqib Nawaz +2 more
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