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   Articles with "itemset mining" as a keyword



A formal series-based unification of the frequent itemset mining approaches

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recommendations! Published in 2017 at "Knowledge and Information Systems"

DOI: 10.1007/s10115-017-1048-y

Abstract: Over the last two decades, a great deal of work has been devoted to the algorithmic aspects of the frequent itemset (FI) mining problem, leading to a phenomenal number of algorithms and associated implementations, each… read more here.

Keywords: itemset mining; mining; frequent itemset; formal series ... See more keywords

Applicable Metamorphic Testing for Erasable-Itemset Mining

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3165656

Abstract: Erasable-itemset mining is often used in production planning to identify itemsets that, if removed, would make little effect on the production profits. Consequently, much recent attention has been focused on increasing the mining efficiency. Yet,… read more here.

Keywords: metamorphic relations; erasable itemset; metamorphic testing; itemset mining ... See more keywords

Efficient Skyline Frequent-Utility Itemset Mining Algorithm on Massive Data

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recommendations! Published in 2024 at "IEEE Transactions on Knowledge and Data Engineering"

DOI: 10.1109/tkde.2024.3349454

Abstract: Frequent itemset mining (FIM) and high-utility itemset mining (HUIM) are two important branches of itemset mining which is a key technology of knowledge discovery in many applications. Nowadays, there have been extensive algorithms on FIM… read more here.

Keywords: utility; utility itemset; skyline frequent; itemset mining ... See more keywords

An Efficient Spark-Based Hybrid Frequent Itemset Mining Algorithm for Big Data

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recommendations! Published in 2022 at "Data"

DOI: 10.3390/data7010011

Abstract: Frequent itemset mining (FIM) is a common approach for discovering hidden frequent patterns from transactional databases used in prediction, association rules, classification, etc. Apriori is an FIM elementary algorithm with iterative nature used to find… read more here.

Keywords: spark; frequent itemset; itemset mining; spark based ... See more keywords

DIAFM: An Improved and Novel Approach for Incremental Frequent Itemset Mining

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recommendations! Published in 2024 at "Mathematics"

DOI: 10.3390/math12243930

Abstract: Traditional approaches to data mining are generally designed for small, centralized, and static datasets. However, when a dataset grows at an enormous rate, the algorithms become infeasible in terms of huge consumption of computational and… read more here.

Keywords: itemset mining; frequent itemset; mining; mining diafm ... See more keywords

Ignoring Internal Utilities in High-Utility Itemset Mining

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recommendations! Published in 2022 at "Symmetry"

DOI: 10.3390/sym14112339

Abstract: 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… read more here.

Keywords: utility values; utility; itemset mining; high utility ... See more keywords