A residual utility-based concept for high-utility itemset mining

Sra, Pushp; Chand, Satish

doi:10.1007/s10115-023-01948-w

Knowl Inf Syst

2023

DOI: 10.1007/s10115-023-01948-w

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A residual utility-based concept for high-utility itemset mining

Pushp Sra,

Satish Chand

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Cited by 2 publications

References 27 publications

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A Reinduction-Based Approach for Efficient High Utility Itemset Mining from Incremental Datasets

Sra,

Chand

2023

Data Sci. Eng.

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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. However, most existing algorithms assume that the databases are static, which is not realistic for real-life datasets that are continuously growing with new data. Furthermore, existing algorithms only rely on the utility value to identify relevant itemsets, leading to even the earliest occurring combinations being produced as output. Although some mining algorithms adopt a support-based approach to account for itemset frequency, they do not consider the temporal nature of itemsets. To address these challenges, this paper proposes the Scented Utility Miner (SUM) algorithm that uses a reinduction strategy to track the recency of itemset occurrence and mine itemsets from incremental databases. The paper provides a novel approach for mining high utility itemsets from dynamic databases and presents several experiments that demonstrate the effectiveness of the proposed approach.

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A Reinduction-Based Approach for Efficient High Utility Itemset Mining from Incremental Datasets

Sra,

Chand

2023

Data Sci. Eng.

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IPHM: Incremental periodic high-utility mining algorithm in dynamic and evolving data environments

Huang,

Chen,

Chen

2024

Heliyon

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A residual utility-based concept for high-utility itemset mining

Cited by 2 publications

References 27 publications

A Reinduction-Based Approach for Efficient High Utility Itemset Mining from Incremental Datasets

A Reinduction-Based Approach for Efficient High Utility Itemset Mining from Incremental Datasets

IPHM: Incremental periodic high-utility mining algorithm in dynamic and evolving data environments

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