Frequent Pattern Mining in Attributed Trees

TitreFrequent Pattern Mining in Attributed Trees
Publication TypeConference Proceedings
Year of Publication2013
AuthorsPasquier, C, Sanhes, J, Flouvat, F, Selmaoui-Folcher, N
Conference NamePacific-Asia Conference on Knowledge Discovery and Data Mining (PaKDD'13)
Volume7818
EditionLecture Notes in Computer Science
PublisherSpringer
Conference LocationGold Coast, Australia
Abstract

Frequent pattern mining is an important data mining task
with a broad range of applications. Initially focused on the discovery
of frequent itemsets, studies were extended to mine structural forms like
sequences, trees or graphs. In this paper, we introduce a new data mining
method that consists in mining new kind of patterns in a collection of
attributed trees (atrees). Attributed trees are trees in which vertices are
associated with itemsets. Mining this type of patterns (called asubtrees),
which combines tree mining and itemset mining, requires the exploration
of a huge search space. We present several new algorithms for attributed
trees mining and show that their implementations can efficiently list
frequent patterns in a database of several thousand of attributed trees.