Results 181 to 190 of about 905 (211)

Pruning strategies for mining high utility itemsets

Expert Systems with Applications, 2015
Presents an efficient high utility mining method.Employs novel pruning strategies to limit the search space of utility mining.Compares the proposed method against a state-of-the-art utility mining method.Experimentally evaluates the system on eight real and synthetic benchmark datasets.Empirical results are found to be quite promising, especially for ...
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Mining local and peak high utility itemsets

Information Sciences, 2019
Abstract A major limitation of traditional High Utility Itemset Mining (HUIM) algorithms is that they do not consider that the utility of itemsets may vary over time. Thus, traditional HUIM algorithms cannot find itemsets that do not yield a high utility when considering the whole database, but still have a high utility during specific time periods ...
Philippe Fournier-Viger, Yimin Zhang, Jerry Chun-Wei Lin, Hamido Fujita, Yun Sing Koh   +4 more
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Targeted High-Utility Itemset Querying

IEEE Transactions on Artificial Intelligence, 2021
Jinbao Miao, Shicheng Wan, Wensheng Gan, Jiayi Sun 0002, Jiahui Chen 0002   +4 more
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PHM: Mining Periodic High-Utility Itemsets

2016
High-utility itemset mining is the task of discovering high-utility itemsets, i.e. sets of items that yield a high profit in a customer transaction database. High-utility itemsets are useful, as they provide information about profitable sets of items bought by customers to retail store managers, which can then use this information to take strategic ...
Philippe Fournier-Viger, Jerry Chun-Wei Lin, Quang-Huy Duong, Thu-Lan Dam   +3 more
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High-Utility Itemset Mining in Big Dataset

2020
High-utility mining (HUIM) is an extended concept from frequent itemset mining (FIM). It emphasizes the more important factors, such as profits or the weight of an itemset in commercial applications. In this paper, we assume a dataset is too big to be loaded in the memory, then propose a MapReduce framework to handle this kind of situation, and try to ...
Jimmy Ming-Tai Wu, Min Wei, Jerry Chun-Wei Lin, Chien-Ming Chen 0001   +3 more
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HMiner: Efficiently mining high utility itemsets

Expert Systems with Applications, 2017
Abstract High utility itemset mining problem uses the notion of utilities to discover interesting and actionable patterns. Several data structures and heuristic methods have been proposed in the literature to efficiently mine high utility itemsets.
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An Efficient Method for Hiding High Utility Itemsets

2013
This paper proposes an algorithm to hide quickly high utility sensitive itemsets. To reduce the execution time, when an item from the sensitive itemset is selected, the rated value is calculated from each transaction containing this item and all values which need be hidden are modified at the same time.
Bay Vo, Chun-Wei Lin 0001, Tzung-Pei Hong, Vinh V. Vu, Minh Nguyen 0004, Bac Le   +5 more
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Parallel High Utility Itemset Mining

2022
Gaojuan Fan, Huaiyuan Xiao, Chongsheng Zhang, George Almpanidis, Philippe Fournier-Viger, Hamido Fujita   +5 more
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Targeted Querying of Closed High-Utility Itemsets

2023 IEEE International Conference on Big Data (BigData), 2023
Shan Huang 0009, Wensheng Gan, Jinbao Miao   +2 more
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Mining On-shelf High-utility Quantitative Itemsets

2021 IEEE International Conference on Big Data (Big Data), 2021
Lili Chen, Wensheng Gan, Qi Lin, Jinbao Miao, Chien-Ming Chen 0001   +4 more
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