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20212026
most citedTaSPM: Targeted Sequential Pattern Mining

6 citations · 15 across the 9 of their papers we have counts for

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8 papers · 1 filter

cs.DB2026

Guided Exploration of Sequential Rules

Wensheng Gan, Gengsen Huang, Junyu Ren +1

In pattern mining, sequential rules provide a formal framework to capture the temporal relationships and inferential dependencies between items. However, the discovery process is c…

cs.DB2026

Discovering High-utility Sequential Rules with Increasing Utility Ratio

Zhenqiang Ye, Wensheng Gan, Gengsen Huang +2

Utility-driven mining is an essential task in data science, as it can provide deeper insight into the real world. High-utility sequential rule mining (HUSRM) aims at discovering se…

cs.DB2023★ 3 cited

TALENT: Targeted Mining of Non-overlapping Sequential Patterns

Zefeng Chen, Wensheng Gan, Gengsen Huang +3

With the widespread application of efficient pattern mining algorithms, sequential patterns that allow gap constraints have become a valuable tool to discover knowledge from biolog…

cs.DB2023

Towards Top- Non-Overlapping Sequential Patterns

Zefeng Chen, Wensheng Gan, Gengsen Huang +2

Sequential pattern mining (SPM) has excellent prospects and application spaces and has been widely used in different fields. The non-overlapping SPM, as one of the data mining tech…

cs.DB2022

Towards Sequence Utility Maximization under Utility Occupancy Measure

Gengsen Huang, Wensheng Gan, Philip S. Yu

The discovery of utility-driven patterns is a useful and difficult research topic. It can extract significant and interesting information from specific and varied databases, increa…

cs.DB2022★ 4 cited

Towards Target Sequential Rules

Wensheng Gan, Gengsen Huang, Jian Weng +2

In many real-world applications, sequential rule mining (SRM) can provide prediction and recommendation functions for a variety of services. It is an important technique of pattern…