Abstract
Many data mining problems can be represented with non-linear data structures like trees. In this paper, we introduce a scalable algorithm to mine partially-ordered trees. Our algorithm, POTMiner, is able to identify both induced and embedded subtrees and, as special cases, it can handle both completely ordered and completely unordered trees (i.e. the particular situations existing algorithms address).
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Jiménez, A., Berzal, F., Cubero, JC. (2008). Mining Induced and Embedded Subtrees in Ordered, Unordered, and Partially-Ordered Trees. In: An, A., Matwin, S., Raś, Z.W., Ślęzak, D. (eds) Foundations of Intelligent Systems. ISMIS 2008. Lecture Notes in Computer Science(), vol 4994. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68123-6_12
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DOI: https://doi.org/10.1007/978-3-540-68123-6_12
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