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Frequent subtree mining : ウィキペディア英語版 | Frequent subtree mining In computer science, frequent subtree mining is the problem of finding all patterns in a given database whose support (a metric related to its number of occurrences in other subtrees) is over a given threshold. It is a more general form of the maximum agreement subtree problem. == Definition == Frequent subtree mining is the problem of trying to find all of the patterns whose "support" is over a certain user-specified level, where "support" is calculated as the number of trees in a database which have at least one subtree isomorphic to a given pattern.〔Dai, H., Srikant, R. and Zhang, C. (2004). "(Advances in Knowledge Discovery and Data Mining. )" ''8th Pacific-Asia Conference, PAKDD 2004, Sydney, Australia, May 26–28, 2004, Proceedings''. 1st ed. p. 65.〕
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