DynamicWEB_AdaptingToDrift.pdf (239.93 kB)
DynamicWEB: Adapting to concept drift in COBWEB
conference contribution
posted on 2023-05-26, 09:30 authored by Joel ScanlanJoel Scanlan, Hartnett, J, Williams, RExamining concepts that change over time has been an active area of research within data mining. This paper presents a new method that functions in contexts where concept drift is present, while also allowing for modification of the instances themselves as they change over time. This method is well suited to domains where subjects of interest are sampled multiple times, and where they may migrate from one resultant concept to another. The method presented here is an extensive modification to the conceptual clustering algorithm COBWEB, and is titled DynamicWEB.
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1Publication status
- Submitted
Event title
21st Australasian Joint Conference on Artifical Intelligence A1-08Event Venue
Auckland, New ZealandDate of Event (Start Date)
2008-12-03Date of Event (End Date)
2008-12-05Repository Status
- Open
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