A nested alignment graph kernel through the dynamic time warping framework

Bai, Lu, Rossi, Luca, Cui, Lixin and Hancock, Edwin R. (2017). A nested alignment graph kernel through the dynamic time warping framework. IN: Graph-based representations in pattern recognition : 11th IAPR-TC-15 international workshop, GbRPR 2017. Proceedings. Foggia, Pasquale; Liu, Cheng-Lin and Vento, Mario (eds) Lecture Notes in Computer Science . Cham (CH): Springer.


In this paper, we propose a novel nested alignment graph kernel drawing on depth-based complexity traces and the dynamic time warping framework. Specifically, for a pair of graphs, we commence by computing the depth-based complexity traces rooted at the centroid vertices. The resulting kernel for the graphs is defined by measuring the global alignment kernel, which is developed through the dynamic time warping framework, between the complexity traces. We show that the proposed kernel simultaneously considers the local and global graph characteristics in terms of the complexity traces, but also provides richer statistic measures by incorporating the whole spectrum of alignment costs between these traces. Our experiments demonstrate the effectiveness and efficiency of the proposed kernel.

Publication DOI: https://doi.org/10.1007/978-3-319-58961-9_6
Divisions: Engineering & Applied Sciences
Engineering & Applied Sciences > Computer science research group
Engineering & Applied Sciences > Systems analytics research institute (SARI)
Event Title: 11th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2017
Event Type: Other
Event Dates: 2017-05-16 - 2017-05-18
Uncontrolled Keywords: Theoretical Computer Science,Computer Science(all)
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
Published Date: 2017
Authors: Bai, Lu
Rossi, Luca ( 0000-0002-6116-9761)
Cui, Lixin
Hancock, Edwin R.



Version: Accepted Version

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