Mining Frequent Diamond Episodes from Event Sequences
نویسندگان
چکیده
In this paper, we introduce a diamond episode of the form s1 → E → s2, where s1 and s2 are events and E is a set of events. The diamond episode s1 → E → s2 means that every event of E follows an event s1 and is followed by an event s2. Then, by formulating the support of diamond episodes, in this paper, we design the algorithm FreqDmd to extract all of the frequent diamond episodes from a given event sequence. Finally, by applying the algorithm FreqDmd to bacterial culture data, we extract diamond episodes representing replacement of bacteria. keywords: data mining in time-related data, episode mining, data min-
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A Polynomial-Delay Polynomial-Space Algorithm for Extracting Frequent Diamond Episodes from Event Sequences
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