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Incremental high average-utility itemset mining: survey and challenges [PDF]
The High Average Utility Itemset Mining (HAUIM) technique, a variation of High Utility Itemset Mining (HUIM), uses the average utility of the itemsets. Historically, most HAUIM algorithms were designed for static databases.
Jing Chen +6 more
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A Reinduction-Based Approach for Efficient High Utility Itemset Mining from Incremental Datasets
High utility itemset mining is a crucial research area that focuses on identifying combinations of itemsets from databases that possess a utility value higher than a user-specified threshold.
Pushp Sra, Satish Chand
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IPHM: Incremental periodic high-utility mining algorithm in dynamic and evolving data environments [PDF]
Periodic high-utility itemset (PHUI) mining can extend beyond the conventional approach of high-utility itemset mining by uncovering recurring customer purchase behaviors common in real-life scenarios (e.g., buying apples and oranges every three days or ...
Huiwu Huang, Shixi Chen, Jiahui Chen
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HUIL-TN & HUI-TN: Mining high utility itemsets based on pattern-growth. [PDF]
In recent years, high utility itemsets (HUIs) mining has been an active research topic in data mining. In this study, we propose two efficient pattern-growth based HUI mining algorithms, called High Utility Itemset based on Length and Tail-Node tree ...
Le Wang, Shui Wang
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Traditional pattern mining algorithms are based on tree and linked list structures. However, they often only consider a single factor of frequency or utility and have to deal with exponential search spaces as well as generate numerous candidates.
Xiumei Zhao, Xincheng Zhong, Bing Han
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A Parallel High-Utility Itemset Mining Algorithm Based on Hadoop
High-utility itemset mining (HUIM) can consider not only the profit factor but also the profitable factor, which is an essential task in data mining. However, most HUIM algorithms are mainly developed on a single machine, which is inefficient for big ...
Zaihe Cheng +3 more
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Ignoring Internal Utilities in High-Utility Itemset Mining
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 ...
Damla Oğuz
openaire +2 more sources
Multi-level high utility-itemset hiding. [PDF]
Privacy is as a critical issue in the age of data. Organizations and corporations who publicly share their data always have a major concern that their sensitive information may be leaked or extracted by rivals or attackers using data miners. High-utility
Loan T T Nguyen +3 more
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A high utility itemsets mining algorithm based on co-evolution [PDF]
Metaheuristic high utility itemsets mining algorithms often face challenges such as poor initial population quality, low time efficiency, and itemsets loss due to premature convergence. To address these issues, this study proposes a high utility itemsets
Wenyan Yang +4 more
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Mining Locally Trending High Utility Itemsets [PDF]
High utility itemset mining consists of identifying all the sets of items that appear together and yield a high profit in a customer transaction database. Recently, this problem was extended to discover trending high utility itemsets (itemsets that yield an increasing or decreasing profit over time).
Fournier-Viger P +3 more
europepmc +3 more sources

