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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 26–39 of 39 papers

TitleStatusHype
Towards Sequence Utility Maximization under Utility Occupancy Measure—0
Using Answer Set Programming for pattern mining—0
Using consumer behavior data to reduce energy consumption in smart homes—0
US-Rule: Discovering Utility-driven Sequential Rules—0
The Crowd in MOOCs: A Study of Learning Patterns at Scale—0
Wisdom of Students: A Consistent Automatic Short Answer Grading Technique—0
A Constraint Programming Approach for Mining Sequential Patterns in a Sequence Database—0
A Fluctuation Smoothing Approach for Unsupervised Automatic Short Answer Grading—0
A global Constraint for mining Sequential Patterns with GAP constraint—0
An Efficient Algorithm for Mining Frequent Sequence with Constraint Programming—0
A Utility-Mining-Driven Active Learning Approach for Analyzing Clickstream Sequences—0
Coupling Knowledge-Based and Data-Driven Systems for Named Entity Recognition—0
Declarative Sequential Pattern Mining of Care Pathways—0
Deep learning-based sequential pattern mining for progressive database—0
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