Efficient Discovery of Weighted Frequent Neighborhood Itemsets in Very Large Spatiotemporal Databases

Efficient Discovery of Weighted Frequent Neighborhood Itemsets in Very Large Spatiotemporal Databases

Weighted Frequent Itemset (WFI) mining is an important model in data mining. It aims to discover all itemsets whose weighted sum in a transactional database is no less than the user-specified threshold value. Most previous works focused on finding WFIs in a transactional database and did not recogni...

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Bibliographic Details
Main Authors: R. Uday Kiran, P. P. C. Reddy, Koji Zettsu, Masashi Toyoda, Masaru Kitsuregawa, P. Krishna Reddy
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Data mining
weighted frequent itemset
pattern-growth technique
spatiotemporal database
Online Access:https://ieeexplore.ieee.org/document/8974289/

Internet

https://ieeexplore.ieee.org/document/8974289/

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