Discrimination Power of Polynomial-Based Descriptors for Graphs by Using Functional Matrices

Matthias Dehmer; Frank Emmert-Streib; Yongtang Shi; Monica Stefu; Shailesh Tripathi

doi:10.1371/journal.pone.0139265

Discrimination Power of Polynomial-Based Descriptors for Graphs by Using Functional Matrices

PLoS One. 2015 Oct 19;10(10):e0139265. doi: 10.1371/journal.pone.0139265. eCollection 2015.

Authors

Matthias Dehmer¹, Frank Emmert-Streib², Yongtang Shi³, Monica Stefu⁴, Shailesh Tripathi⁵

Affiliations

¹ Department of Computer Science, Universität der Bundeswehr München, Werner-Heisenberg-Weg 39, 85577 Neubiberg, Germany; Department of Mechatronics and Biomedical Computer Science UMIT, Eduard Wallnoefer Zentrum 1, A-6060, Hall in Tyrol, Austria.
² Computational Medicine and Statistical Learning Laboratory, Department of Signal Processing, Tampere University of Technology, Korkeakoulunkatu 1, FI-33720 Tampere, Finland.
³ Center for Combinatorics and LPMC-TJKLC, Nankai University, Tianjin, 300071, P.R. China.
⁴ Department of Mechatronics and Biomedical Computer Science UMIT, Eduard Wallnoefer Zentrum 1, A-6060, Hall in Tyrol, Austria.
⁵ School of Mathematics and Physics, Queen's University Belfast, University Road, Belfast, BT7 1NN, United Kingdom.

Abstract

In this paper, we study the discrimination power of graph measures that are based on graph-theoretical matrices. The paper generalizes the work of [M. Dehmer, M. Moosbrugger. Y. Shi, Encoding structural information uniquely with polynomial-based descriptors by employing the Randić matrix, Applied Mathematics and Computation, 268(2015), 164-168]. We demonstrate that by using the new functional matrix approach, exhaustively generated graphs can be discriminated more uniquely than shown in the mentioned previous work.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Computer Graphics*
Mathematics / methods*

Grants and funding

Matthias Dehmer thanks the Austrian Science Funds for supporting this work (project P26142). Yongtang Shi is supported by NSFC, PCSIRT, China Postdoctoral Science Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.