Graph Theoretic Concepts in Data Science
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Network Science".
Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 8200
Special Issue Editor
Interests: algorithmic and structural graph theory; graph-based data science; diffusion models in graphs; network analysis and mining; network optimisation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
During recent years, the mining of unstructured data has become a relevant field both in science and practical applications. Among seemingly unstructured datasets, hidden graph structures have proven to be very useful in analysis. The graph representation of these data makes it possible to use powerful methods of graph data science and also provides inspiration to develop new methods.
Network science and graph mining became the key disciplines to provide the methodology for processing and analysing of graph structured data. The powerful methods of the above fields have made it possible to discover the patterns and describe the dynamics of networked systems. On the other hand, though the classical field of graph theory ensures the modelling framework, the recent progress in discrete models and methods, such as algorithmic and structural graph theory, still has limited use in data science.
The aim of this Special Issue is to provide a forum for researchers in graph theory and data science to share their original results on the integrated use of both fields. Graph theoretic papers motivated by data science problems as well as data science applications based on graph theoretic solutions will both be considered.
Prof. Dr. Miklós Krész
Guest Editor
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 submissions that pass pre-check are 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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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.
Keywords
- data science
- graph models
- graph algorithms
- network analytics
- big data problems
- large graphs
- computational complexity
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue polices can be found here.