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<span class="MathJax_Preview">K</span><script type="math/tex" id="MathJax-Element-1">K</script> -Ary Tree Hashing for Fast Graph Classification | IEEE Journals & Magazine | IEEE Xplore

K -Ary Tree Hashing for Fast Graph Classification


Abstract:

Existing graph classification usually relies on an exhaustive enumeration of substructure patterns, where the number of substructures expands exponentially w.r.t. with th...Show More

Abstract:

Existing graph classification usually relies on an exhaustive enumeration of substructure patterns, where the number of substructures expands exponentially w.r.t. with the size of the graph set. Recently, the Weisfeiler-Lehman (WL) graph kernel has achieved the best performance in terms of both accuracy and efficiency among state-of-the-art methods. However, it is still time-consuming, especially for large-scale graph classification tasks. In this paper, we present a K-Ary Tree based Hashing (KATH) algorithm, which is able to obtain competitive accuracy with a very fast runtime. The main idea of KATH is to construct a traversal table to quickly approximate the subtree patterns in WL using K-ary trees. Based on the traversal table, KATH employs a recursive indexing process that performs only r times of matrix indexing to generate all (r - 1)-depth K-ary trees, where the leaf node labels of a tree can uniquely specify the pattern. After that, the MinHash scheme is used to fingerprint the acquired subtree patterns for a graph. Our experimental results on both real world and synthetic data sets show that KATH runs significantly faster than state-of-the-art methods while achieving competitive or better accuracy.
Published in: IEEE Transactions on Knowledge and Data Engineering ( Volume: 30, Issue: 5, 01 May 2018)
Page(s): 936 - 949
Date of Publication: 11 December 2017

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