I. McLaren, E. Babb and J. Bocca. DAFS: supporting the knowledge discovery process. Proc. 1st Int. Conf. Practical Applications of Knowledge Discovery and Data Mining (PADD'97), 179-190. The Practical Application Company, UK. Apr. 1997. Home/Search Document Details and Download
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PKDD'98 Tutorial on Scalable, High-Performance Data Mining with.. - Freitas (1998) (Correct)
.... mining (b) many data warehouses are already implemented on parallel database servers (c) offers a kind of automatic parallelization Main Disadvantages: a) programmer has less control over parallelization (b) overhead of the DBMS kernel Parallel rule induction with DBMS facilities DAFS project [McLaren et al. 97] parallel database server designed to support the overal knowledge discovery process. Client: Clementine data mining tool Server: shared nothing parallel DB server Parallel beam search [Holsheimer et al. 96] Basic idea: candidate rules are evaluated by submitting queries to parallel DB server ....
I. McLaren, E. Babb and J. Bocca. DAFS: supporting the knowledge discovery process. Proc. 1st Int. Conf. Practical Applications of Knowledge Discovery and Data Mining (PADD'97), 179-190. The Practical Application Company, UK. Apr. 1997.
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....to predict the queries generated during data mining. Support for unpredictable queries is achieved by general purpose multi dimensional indexing techniques found in spatial and advanced database systems. This type of index needs to be available if database mining algorithms are to be successful [6]. Extracting meaningful models from very large sets of data is a complex, and time consuming task. Most conventional artificial intelligence algorithms are unable to support these sizes of database. One technique which has been developed to overcome this problem is the use of incremental learning. ....
I. McLaren, E. Babb and J. Bocca. DAFS: Supporting the knowledge discovery process. In: Proceedings of First International Conference on Practical Applications of Knowledge Discovery and Data Mining, London, UK, April 1997.
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