Advertisement
Published in:
2005 | OriginalPaper | Chapter
Interactive Comprehensible Data Mining
Authors : Andy Pryke, Russell Beale
Published in: Ambient Intelligence for Scientific Discovery
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
In data mining, or knowledge discovery, we are essentially faced with a mass of data that we are trying to make sense of. We are looking for something “interesting”. Quite what “interesting” means is hard to define, however – one day it is the general trend that most of the data follows that we are intrigued by – the next it is why there are a few outliers to that trend. In order for a data mining to be generically useful to us, it must therefore have some way in which we can indicate what is interesting and what is not, and for that to be dynamic and changeable.