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 …
world applications. It involves extracting all itemsets exhibiting stable periodic behaviors in a …
3P-ECLAT: mining partial periodic patterns in columnar temporal databases
V Pamalla, UK Rage, R Penugonda, L Palla… - Applied …, 2024 - Springer
Partial periodic pattern (3P) mining is a vital data mining technique that aims to discover all
interesting patterns that have exhibited partial periodic behavior in temporal databases …
interesting patterns that have exhibited partial periodic behavior in temporal databases …
A fundamental approach to discover closed periodic-frequent patterns in very large temporal databases
V Pamalla, UK Rage, R Penugonda, L Palla… - Applied …, 2023 - Springer
Periodic frequent-pattern mining (PFPM) is a vital knowledge discovery technique that
identifies periodically occurring patterns in a temporal database. Although traditional PFPM …
identifies periodically occurring patterns in a temporal database. Although traditional PFPM …
k-PFPMiner: Top-k Periodic Frequent Patterns in Big Temporal Databases
Finding periodic-frequent patterns in temporal databases is a prominent data mining
problem with bountiful applications. It involves discovering all patterns in a database that …
problem with bountiful applications. It involves discovering all patterns in a database that …