.png){kind=icon}
Return
Mining association rules on significant rare data using relative support
.png){kind=icon}
PRE
AI
DOI：10.1016/S0164-1212(02)00128-0.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Recently, data mining, a technique to analyze the stored data in large databases to discover potential information and knowledge, has been a popular topic in database research. In this paper, we study the techniques discovering the association rules which are one of these data mining techniques. And we propose a technique discovering the association rules for significant rare data that appear infrequently in the database but are highly associated with specific data. Furthermore, considering these significant rare data, we evaluate the performance of the proposed algorithm by comparing it with other existing algorithms for discovering the association rules. (C) 2002 Elsevier Inc. All rights reserved.
Keywords:
data mining
potential information
association rules
significant rare data
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.1
Papers:
5.5K
Citations:
8.4K
Organization
No organization information available
Cited Papers
.png){kind=icon}
ShareSave
ShareSaveShareSave no more
no more