@article{6169a06b22d84751bb2c7b7fd3835dcd,
title = "Properties of Graph Distance Measures by Means of Discrete Inequalities",
abstract = "In this paper, we investigate graph distance measures based on topological graph measures. Those measures can be used to measure the structural distance between graphs. When studying the scientific literature, one is aware that measuring distance/similarity between graphs meaningfully has been intricate. We demonstrate that our measures are well-defined and prove bounds for investigating their value domain. Also, we generate numerical results and demonstrate that the measures have useful properties.",
keywords = "Distance measures, Graphs, Inequalities, Networks, Similarity measures",
author = "Matthias Dehmer and Zengqiang Chen and Frank Emmert-Streib and Yongtang Shi and Shailesh Tripathi and Aliyu Musa and Abbe Mowshowitz",
note = "Funding Information: Matthias Dehmer thanks the Austrian Science Funds for supporting this work (project P26142). Zengqiang Chen was supported by the National Science Foundation of China (No. 61573199 ) and the Natural Science Foundation of Tianjin (No. 14JCYBJC18700 ). Yongtang Shi was partially supported by the Natural Science Foundation of Tianjin (No. 17JCQNJC00300 ) and National Natural Science Foundation of China. Publisher Copyright: {\textcopyright} 2018 Elsevier Inc. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.",
year = "2018",
month = jul,
doi = "10.1016/j.apm.2018.01.027",
language = "English",
volume = "59",
pages = "739--749",
journal = "Applied Mathematics Modelling",
}