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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
Leveraging Language Foundation Models for Human Mobility ForecastingCode1
Causal Analysis of Customer Churn Using Deep LearningCode1
The Crowd in MOOCs: A Study of Learning Patterns at Scale—0
Coupling Knowledge-Based and Data-Driven Systems for Named Entity Recognition—0
A Fluctuation Smoothing Approach for Unsupervised Automatic Short Answer Grading—0
A Utility-Mining-Driven Active Learning Approach for Analyzing Clickstream Sequences—0
A global Constraint for mining Sequential Patterns with GAP constraint—0
A Constraint Programming Approach for Mining Sequential Patterns in a Sequence Database—0
An Efficient Algorithm for Mining Frequent Sequence with Constraint Programming—0
Declarative Sequential Pattern Mining of Care Pathways—0
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