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Special Issue "Graph Entropy and Its Applications"
A special issue of Entropy (ISSN 1099-4300).
Deadline for manuscript submissions: 30 November 2019.
Prof. Dr. Matthias M. Dehmer Website E-Mail
1. University of Applied Sciences Upper Austria, Campus Steyr, Wehrgrabengasse 1, 4040 Steyr, Austria
2. College of Artificial Intelligence,Nankai University, Tianjin 300071, China
Interests: applied mathematics; bioinformatics; data mining; machine learning; systems biology; graph theory; complexity and information theory
Prof. Dr. Shenggui Zhang E-Mail
Department of Applied Mathematics, Northwestern Polytechnical University, Xi'an, Shaanxi 710072, China
Interests: graphs and networks
Prof. Dr. Abbe Mowshowitz Website E-Mail
Department of Computer Science, The City College of New York, New York, NY 10031, USA
Interests: network science; complexity of graphs and networks; dynamic distributed database systems; virtual organization; management and economics of information
Prof. Dr. Yongtang Shi E-Mail
Center for Combinatorics, Nankai University, Tianjin 300071, China
Interests: graph theory and its applications; combinatorial optimization
Prof. Dr. Zengqiang Chen E-Mail
College of Computer and Control Engineering, Nankai University, Tianjin 300071, China
Interests: intelligent optimizing control; intelligent computing; complex networks; multiagent systems
Information theory provides several measures to assess the complex systems associated with graphs and networks. These measures are based on Claude Shannon’s well known entropy measure, which allows for quantifying the structural information content of a network. Quantitative values obtained in this way reflect underlying graph topology and serve as measures of graph complexity. However, such measures are relative to particular structural features, and thus it may be said that graph complexity is “in the eye of the beholder.” This accounts in large part for the proliferation of entropy and related information-theoretic measures defined on graphs.
Many research papers have introduced entropy measures based on graph invariants. Thus, the literature abounds with analytical results, studies of correlations between network properties and quantitative values, and investigations into the uniqueness of entropy measures.
This Special Issue invites contributions that present new and original research based on the use of information-theoretic graph measures. Analytical contributions proving properties/relations or their application to any kind of data are welcome. Manuscripts reviewing the most recent state-of-the-art research on this topic will also be considered.
Prof. Matthias M. Dehmer
Prof. Dr. Shenggui Zhang
Prof. Dr. Abbe Mowshowitz
Prof. Dr. Frank Emmert-Streib
Prof. Dr. Yongtang Shi
Prof. Dr. Zengqiang Chen
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.