IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v175y2023ip1s096007792300841x.html
   My bibliography  Save this article

Temporal metagraph: A new mathematical approach to capture temporal dependencies and interactions between different entities over time

Author

Listed:
  • Iglesias-Perez, Sergio
  • Criado, Regino

Abstract

Predicting real estate prices is a difficult task that requires consideration of various factors and their dynamic interactions over time. In this study, based on the introduction of a new mathematical structure called temporal metagraph, we use a novel approach that exploits the properties of this structure to predict real estate prices in Helsinki by integrating information derived from bicycle trips. The temporal metagraph concept intrinsically captures temporal dependencies and interactions between different entities or agents (nodes of the metagraph), allowing us to model and analyze different real situations and, in particular, the dynamic relationships between bicycle commuting and real estate prices. Our experimental results demonstrate the effectiveness of the proposed approach, as more accurate and reliable predictions are achieved than traditional models, which are based solely on historical price data.

Suggested Citation

  • Iglesias-Perez, Sergio & Criado, Regino, 2023. "Temporal metagraph: A new mathematical approach to capture temporal dependencies and interactions between different entities over time," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    • Handle: RePEc:eee:chsofr:v:175:y:2023:i:p1:s096007792300841x
    DOI: 10.1016/j.chaos.2023.113940
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096007792300841X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2023.113940?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rahul Goel & Anna Goodman & Rachel Aldred & Ryota Nakamura & Lambed Tatah & Leandro Martin Totaro Garcia & Belen Zapata-Diomedi & Thiago Herick de Sa & Geetam Tiwari & Audrey de Nazelle & Marko Tainio, 2022. "Cycling behaviour in 17 countries across 6 continents: levels of cycling, who cycles, for what purpose, and how far?," Transport Reviews, Taylor & Francis Journals, vol. 42(1), pages 58-81, January.
    2. Iglesias Pérez, Sergio & Moral-Rubio, Santiago & Criado, Regino, 2021. "A new approach to combine multiplex networks and time series attributes: Building intrusion detection systems (IDS) in cybersecurity," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    3. Petter Holme, 2015. "Modern temporal network theory: a colloquium," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(9), pages 1-30, September.
    4. Pérez, Sergio Iglesias & Moral-Rubio, Santiago & Criado, Regino, 2023. "Combining multiplex networks and time series: A new way to optimize real estate forecasting in New York using cab rides," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Anzhi Sheng & Qi Su & Aming Li & Long Wang & Joshua B. Plotkin, 2023. "Constructing temporal networks with bursty activity patterns," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    2. Panayotis Christidis & Álvaro Gomez Losada, 2019. "Email Based Institutional Network Analysis: Applications and Risks," Social Sciences, MDPI, vol. 8(11), pages 1-14, November.
    3. Timmons, Shane & Andersson, Ylva & McGowan, Féidhlim & Lunn, Pete, 2023. "Using behavioural science to design and implement active travel infrastructure: A narrative review of evidence," Papers WP745, Economic and Social Research Institute (ESRI).
    4. Dantsuji, Takao & Sugishita, Kashin & Fukuda, Daisuke, 2023. "Understanding changes in travel patterns during the COVID-19 outbreak in the three major metropolitan areas of Japan," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    5. Echeverría, Lucía & Giménez-Nadal, J. Ignacio & Alberto Molina, José, 2022. "Who uses green mobility? Exploring profiles in developed countries," Transportation Research Part A: Policy and Practice, Elsevier, vol. 163(C), pages 247-265.
    6. Hongyong Wang & Ping Xu & Fengwei Zhong, 2022. "Modeling and Feature Analysis of Air Traffic Complexity Propagation," Sustainability, MDPI, vol. 14(18), pages 1-21, September.
    7. Pietro DeLellis & Anna DiMeglio & Franco Garofalo & Francesco Lo Iudice, 2017. "The evolving cobweb of relations among partially rational investors," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-21, February.
    8. Mathilde Vernet & Yoann Pigné & Éric Sanlaville, 2023. "A study of connectivity on dynamic graphs: computing persistent connected components," 4OR, Springer, vol. 21(2), pages 205-233, June.
    9. Karan, Rituraj & Biswal, Bibhu, 2017. "A model for evolution of overlapping community networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 380-390.
    10. Li, Mingwu & Dankowicz, Harry, 2019. "Impact of temporal network structures on the speed of consensus formation in opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1355-1370.
    11. Sindhuja Ranganathan & Mikko Kivelä & Juho Kanniainen, 2018. "Dynamics of investor spanning trees around dot-com bubble," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-14, June.
    12. Sergio Iglesias Perez & Regino Criado, 2022. "Increasing the Effectiveness of Network Intrusion Detection Systems (NIDSs) by Using Multiplex Networks and Visibility Graphs," Mathematics, MDPI, vol. 11(1), pages 1-24, December.
    13. José Ignacio Giménez-Nadal & Lucía Echeverría & Alberto Molina, 2023. "Citizen security and urban commuting in Latin America," Urban Studies, Urban Studies Journal Limited, vol. 60(13), pages 2585-2611, October.
    14. Chae, Bongsug (Kevin), 2019. "A General framework for studying the evolution of the digital innovation ecosystem: The case of big data," International Journal of Information Management, Elsevier, vol. 45(C), pages 83-94.
    15. Andrew Mellor, 2019. "Event Graphs: Advances And Applications Of Second-Order Time-Unfolded Temporal Network Models," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(03), pages 1-26, May.
    16. Christos Ellinas & Christos Nicolaides & Naoki Masuda, 2022. "Mitigation strategies against cascading failures within a project activity network," Journal of Computational Social Science, Springer, vol. 5(1), pages 383-400, May.
    17. Zhu, He & Ma, Jing, 2018. "Knowledge diffusion in complex networks by considering time-varying information channels," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 225-235.
    18. Radu Tanase & Claudio J Tessone & René Algesheimer, 2018. "Identification of influencers through the wisdom of crowds," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-15, July.
    19. Tao, Li & Kong, Shengzhou & He, Langzhou & Zhang, Fan & Li, Xianghua & Jia, Tao & Han, Zhen, 2022. "A sequential-path tree-based centrality for identifying influential spreaders in temporal networks," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    20. Mitja Steinbacher & Matthias Raddant & Fariba Karimi & Eva Camacho Cuena & Simone Alfarano & Giulia Iori & Thomas Lux, 2021. "Advances in the agent-based modeling of economic and social behavior," SN Business & Economics, Springer, vol. 1(7), pages 1-24, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:175:y:2023:i:p1:s096007792300841x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.