DocumentCode
823499
Title
Data mining for very busy people
Author
Menzies, Tim ; Hu, Ying
Author_Institution
West Virginia Univ., Morgantown, WV, USA
Volume
36
Issue
11
fYear
2003
Firstpage
22
Lastpage
29
Abstract
Most modern businesses can access mountains of data electronically; the trick is effectively using that data. In practice, this means summarizing large data sets to find the data that really matters. Most data miners are zealous hunters seeking detailed summaries and generating extensive and lengthy descriptions. The authors take a different approach and assume that busy people don´t need, or can´t use complex models. Rather, they want only the data they need to achieve the most benefits. Instead of finding extensive descriptions of things, their data mining tool hunts for a minimal difference set between things because they believe a list of essential differences is easier to read and understand than detailed descriptions.
Keywords
data mining; decision trees; learning (artificial intelligence); data miners; data mining tool; detailed summaries; large data sets; minimal difference set; modern businesses; very busy people; zealous hunters; Assembly; Association rules; Classification tree analysis; Data mining; Databases; Decision making; Decision trees; Humans; Machine learning; World Wide Web;
fLanguage
English
Journal_Title
Computer
Publisher
ieee
ISSN
0018-9162
Type
jour
DOI
10.1109/MC.2003.1244531
Filename
1244531
Link To Document