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Sequential Pattern Mining

Sequential Pattern Mining is the process that discovers relevant patterns between data examples where the values are delivered in a sequence.

Source: Big Data Analytics for Large Scale Wireless Networks: Challenges and Opportunities

Papers

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Showing 1–10 of 39 papers

TitleStatusHype
Causal Analysis of Customer Churn Using Deep LearningCode1
Leveraging Language Foundation Models for Human Mobility ForecastingCode1
A Utility-Mining-Driven Active Learning Approach for Analyzing Clickstream Sequences—0
The Crowd in MOOCs: A Study of Learning Patterns at Scale—0
Mining compact high utility sequential patternsCode0
Sequential pattern mining in educational data: The application context, potential, strengths, and limitations—0
HUSP-SP: Faster Utility Mining on Sequence DataCode0
Towards Sequence Utility Maximization under Utility Occupancy Measure—0
Towards Correlated Sequential Rules—0
Totally-ordered Sequential Rules for Utility Maximization—0
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