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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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Approximate Parallel High Utility Itemset Mining [PDF]
Big Data Research, 2016 High utility itemset mining discovers itemsets whose utility is above a given threshold, where the utility measures the importance of an itemset. It overcomes the limitation of frequent pattern mining, which uses frequency as its quality measure. To speed up the performance for mining high utility itemsets, many algorithms have been proposed which ...
Yan Chen, Aijun An
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TUB-HAUPM: Tighter Upper Bound for Mining High Average-Utility Patterns
IEEE Access, 2018 High-utility itemset mining (HUIM) has been gaining popularity in the field of data mining. Frequent itemset mining used to be the main tool to reveal high-frequency patterns but failed to consider the concept of profit.
Jimmy Ming-Tai Wu +3 more
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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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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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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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Efficient Analysis of Pattern and Association Rule Mining Approaches
, 2014 The process of data mining produces various patterns from a given data source. The most recognized data mining tasks are the process of discovering frequent itemsets, frequent sequential patterns, frequent sequential rules and frequent association rules.
Lazzez, Amor, Slimani, Thabet
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IEEE Access, 2021 Utility-pattern mining in data has received a lot of attention from the knowledge discovery in database (KDD) community due to its high potential for many applications such as finance, biomedicine, manufacturing, e-commerce, and social media.
Jerry Chun-Wei Lin +3 more
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Maximizing Welfare in Social Networks under a Utility Driven Influence Diffusion Model
, 2019 Motivated by applications such as viral marketing, the problem of influence maximization (IM) has been extensively studied in the literature. The goal is to select a small number of users to adopt an item such that it results in a large cascade of ...
Abramowitz B. +6 more
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An efficient parallel method for mining frequent closed sequential patterns [PDF]
, 2017 Mining frequent closed sequential pattern (FCSPs) has attracted a great deal of research attention, because it is an important task in sequences mining.
Huynh, Bao, Snášel, Václav, Vo, Bay
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