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Mining unordered embedded patterns TreeFinder [17] is the first unordered embedded tree pattern mining algorithm.
Our results show that maximal homomorphic patterns are fewer and larger than maximal embedded tree patterns.
This problem departs from previous ones which focus on mining-induced or embedded tree patterns from a set of small data trees.
EmbTreeMiner is a newer embedded tree mining algorithm which, as HomTreeMiner, exploits the twig-join approach and bitmaps to compute pattern support.
The experimental evaluation shows that our approach mines larger patterns and extracts maximal homomorphic patterns from real and synthetic datasets outperforming state-of-the-art embedded tree mining algorithms applied to a large data tree.
The only known papers are [8, 10, 11] which focus on mining tree patterns with only child edges from a single graph and [19] which leverages homomorphisms to mine embedded tree patterns from a single tree.
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Further, our algorithm is as fast as the state-of-the-art algorithm mining embedded trees from a single tree while outperforming it in terms of memory consumption and scalability.
Hence, they present a unified framework for binary recursive partitioning which embeds tree-structured regression models into a well-defined theory of conditional inference procedures.
This paper is a proposal to embed tree-shaped vasculatures in a wall designed such that the wall withstands without excessive hot spots the intense heating that impinges on it.
And at Por Los Siglos, a jewelry store, I found a beautiful handmade silver bracelet embedded with tree bark.
The event will also celebrate the Tree Ring Lab's 25th anniversary "with exhibits on the stories embedded in tree rings," he said.
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