Mining algorithm for weighted FP-tree frequent item sets based on two-dimensional table

Autor:	Yuanyuan Li, Shaohong Yin
Rok vydání:	2020
Předmět:	History Tree (data structure) Computer science Table (database) Data mining computer.software_genre computer Data mining algorithm Computer Science Applications Education
Zdroj:	Journal of Physics: Conference Series. 1453:012002
ISSN:	1742-6596 1742-6588
DOI:	10.1088/1742-6596/1453/1/012002
Popis:	FP-growth algorithm is a classic algorithm of mining frequent item sets, but there exist certain disadvantages for mining the weighted frequent item sets. Based on the weighted downward closure property of the weighted model, this paper proposed that the weighted support was recorded in the two-dimensional table. This method has saved the process to search for the first conditional pattern base by traversing the weighted FP-tree, improved the efficiency of the weighted frequent item sets generated.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::bf890d9c30e12082a645a520fcf8fcdc https://doi.org/10.1088/1742-6596/1453/1/012002 Zobrazit plný text záznamu