MINING CONDENSED SETS OF FREQUENT EPISODES WITH MORE ACCURATE FREQUENCIES FROM COMPLEX SEQUENCES
作者： Honghua Dai , Min Gan
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摘要: Many previous approaches to frequent episode discovery only accept sim- ple sequences. Although a recent approach has been able tond episodes from complex sequences, the discovered sets are neither condensed nor accurate. This paper investigates of We adopt novel anti-monotonic frequency measure based on non-redundant occurrences, and dene set, nDaCF (the set non-derivable approximately closed fre- quent episodes) within given maximal error bound support. then introduce series effective pruning strategies, develop method, - Miner, for discov- ering sets. Experimental results show that, when is somewhat high, two orders magnitude smaller than complete sets, nDaCF-miner more efficient mining approaches. In addition, accurate found by Keywords: Frequent episodes, Condensed Sequence data
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