http://hdl.handle.net/1893/37757| Appears in Collections: | Computing Science and Mathematics Book Chapters and Sections |
| Peer Review Status: | Refereed |
| Title: | Graph Pseudometrics from a Topological Point of View |
| Author(s): | Garcia-Pulido, Ana Lucia Hess, Kathryn Tan, Jane Turner, Katharine Wang, Bei Yerolemou, Naya |
| Contact Email: | analucia.garciapulido@stir.ac.uk |
| Editor(s): | Gasparovic, Ellen Robins, Vanessa Turner, Katharine |
| Sponsor: | Australian Research Council National Science Foundation National Science Foundation Engineering and Physical Sciences Research Council Engineering and Physical Sciences Research Council |
| Citation: | Garcia-Pulido AL, Hess K, Tan J, Turner K, Wang B & Yerolemou N (2023) Graph Pseudometrics from a Topological Point of View. In: Gasparovic E, Robins V & Turner K (eds.) <i>Research in Computational Topology 2</i>. Association for Women in Mathematics Series. Springer International Publishing, pp. 99-128. https://doi.org/10.1007/978-3-030-95519-9_5 |
| Issue Date: | 2023 |
| Date Deposited: | 29-Nov-2024 |
| Series/Report no.: | Association for Women in Mathematics Series |
| Abstract: | We explore pseudometrics for directed graphs in order to better understand their topological properties. The directed flag complex associated to a directed graph provides a useful bridge between network science and topology. Indeed, it has often been observed that phenomena exhibited by real-world networks reflect the topology of their flag complexes, as measured, for example, by Betti numbers or simplex counts. As it is often computationally expensive (or even unfeasible) to determine such topological features exactly, it would be extremely valuable to have pseudometrics on the set of directed graphs that can both detect the topological differences and be computed efficiently. To facilitate work in this direction, we introduce methods to measure how well a graph pseudometric captures the topology of a directed graph. We then use these methods to evaluate some well-established pseudometrics, using test data drawn from several families of random graphs. |
| DOI Link: | 10.1007/978-3-030-95519-9_5 |
| Licence URL(s): | http://www.rioxx.net/licenses/under-embargo-all-rights-reserved |
| File | Description | Size | Format | |
|---|---|---|---|---|
| Graph_Pseudometrics.pdf | Fulltext - Accepted Version | 842.32 kB | Adobe PDF | Under Permanent Embargo Request a copy |
Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.
This item is protected by original copyright |
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved https://creativecommons.org/publicdomain/zero/1.0/
If you believe that any material held in STORRE infringes copyright, please contact library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.
