Abstract
Association rules mining is a basic method in data mining.This paper first introduces the basic concepts of association rules mining and Apriori algorithm. It also provides a parallel association rules model scheme for improving the mining efficiency when treating large numbers of data sets as well as the analyse of the scheme effect. In conclusion we discuss how to apply association rules mining to insurance data sets, find out the knowledge hidden behind the data sets, and provide powerful decision-making support for people.
This research is supported by a joint research grant from National Science Foundation of China (project No.60131160743) and Hong Kong Research Grant Council.
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Tian, J., Zhu, L., Zhang, S., Huang, G. (2004). Parallelism of Association Rules Mining and Its Application in Insurance Operations. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds) Computational Science - ICCS 2004. ICCS 2004. Lecture Notes in Computer Science, vol 3039. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25944-2_117
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DOI: https://doi.org/10.1007/978-3-540-25944-2_117
Publisher Name: Springer, Berlin, Heidelberg
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