Guiding Knowledge Discovery Through Interactive Data Mining
Aaron Ceglar (Flinders University, South Australia), John Roddick (Flinders University, South Australia) and Paul Calder (Flinders University, South Australia)
Copyright: © 2003
Knowledge discovery is the process of eliciting interesting knowledge from data repositories. Due to the inability of computers to understand abstract concepts, present mining algorithms do not adequately constrain the generation of rules to those that are of interest to the user. Interactive mining techniques aim to alleviate this problem by involving the user in the mining process, so that the user’s understanding of abstract semantic concepts and domain knowledge can guide the discovery process, resulting in accelerated mining with improved results. This chapter presents a discussion of the current state of interactive data mining research.