Generic Pattern Mining Via Data Mining Template Library
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases(2004)
摘要
Frequent Pattern Mining (FPM) is a very powerful paradigm for mining informative and useful patterns in massive, complex datasets. In this paper we propose the Data Mining Template Library, a collection of generic containers and algorithms for data mining, as well as persistency and database management classes. DMTL provides a systematic solution to a whole class of common FPM tasks like itemset, sequence, tree and graph mining. DMTL is extensible, scalable, and high-performance for rapid response on massive datasets. A detailed set of experiments show that DMTL is competitive with special purpose algorithms designed for a particular pattern type, especially as database sizes increase.
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关键词
data mining,graph mining,Data Mining Template Library,Frequent Pattern Mining,common FPM task,complex datasets,database management class,database sizes increase,massive datasets,detailed set,generic pattern mining,template library
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