Title :
Data mining for very busy people
Author :
Menzies, Tim ; Hu, Ying
Author_Institution :
West Virginia Univ., Morgantown, WV, USA
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;
DOI :
10.1109/MC.2003.1244531