Finding Stable Periodic-Frequent Itemsets in Big Columnar Databases

Finding Stable Periodic-Frequent Itemsets in Big Columnar Databases

Stable periodic-frequent itemset mining is essential in big data analytics with many real-world applications. It involves extracting all itemsets exhibiting stable periodic behaviors in a temporal database. Most previous studies focused on finding these itemsets in row (temporal) databases and disre...

Full description

Bibliographic Details
Main Authors: Hong N. Dao, Penugonda Ravikumar, Palla Likhitha, Uday Kiran Rage, Yutaka Watanobe, Incheon Paik
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Columnar databases
stable periodic-frequent itemset
itemset mining
Online Access:https://ieeexplore.ieee.org/document/10034746/

Internet

https://ieeexplore.ieee.org/document/10034746/

Similar Items