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Predicting water-conducting fracture zone height in three-soft coal seams using a BOA-MLP model. [PDF]

Sci Rep
Tang Z, Tong H, Zhang D, Fan G, Ren C, Sun Y, Gao X, Zhang Y, Wu Z.   +8 more
europepmc   +1 more source

Value Chain Analysis and Strategic Framework for Economic Upgrading in North Macedonia’s Critical Minerals Sector

Kiselicki M, Haneklaus N, Santa M, Josimovski S, Jovevski D, Ivanovska LP, Blagoeva KT, Belshoska MM, Josimovska T, Nikolov AJ.   +9 more
europepmc   +1 more source

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HIGH UTILITY ITEMSETS MINING

International Journal of Information Technology & Decision Making, 2010
High utility itemsets mining identifies itemsets whose utility satisfies a given threshold. It allows users to quantify the usefulness or preferences of items using different values. Thus, it reflects the impact of different items. High utility itemsets mining is useful in decision-making process of many applications, such as retail marketing and Web ...
YING LIU, JIANWEI LI, WEI-KENG LIAO, ALOK CHOUDHARY, YONG SHI   +4 more
openaire   +3 more sources

Mining Utility Patterns

2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), 2018
’Data mining’ itself explains that it is the mining of data from large reserve of data generated every day. Business uses data mining to make important decisions to increase their revenue, increase the potential customer base, reduce costs etc. In the retail industry, useful pattern discovery is essential out of huge amount of data is generated ...
Ashmita Saha, Vaishali D. Khairnar
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Mining Utility Association Rules

Proceedings of the 2018 10th International Conference on Computer and Automation Engineering, 2018
Mining high utility itemset is to find the itemsets that can bring higher profits to the company, which considers both of the profits and purchased quantities for the items. However, from the high utility itemsets, we cannot know what products should be recommended to the customer such that the profit can be increased when he/she bought some products ...
Yue-Shi Lee, Show-Jane Yen
openaire   +1 more source

Mining high utility itemsets

Third IEEE International Conference on Data Mining, 2004
Traditional association rule mining algorithms only generate a large number of highly frequent rules, but these rules do not provide useful answers for what the high utility rules are. We develop a novel idea of top-K objective-directed data mining, which focuses on mining the top-K high utility closed patterns that directly support a given business ...
null Raymond Chan, null Qiang Yang, null Yi-Dong Shen   +2 more
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Utility-Driven Mining of High Utility Episodes

2019 IEEE International Conference on Big Data (Big Data), 2019
Sequence data, e.g., complex event sequence, is more commonly seen than other types of data (e.g., transaction data) in real-world applications. For the mining task from sequence data, several problems have been formulated, such as sequential pattern mining, episode mining, and sequential rule mining.
Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao, Philip S. Yu   +3 more
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Mining Skyline Frequent-Utility Itemsets with Utility Filtering

2021
Skyline frequent-utility itemsets (SFUIs) can provide more actionable information for decision-making with both frequency and utility considered. In this paper, the problem of mining SFUIs by filtering utilities from different perspectives is studied. First, filtering by frequency is considered.
Wei Song, Chuanlong Zheng, Philippe Fournier-Viger   +2 more
openaire   +1 more source