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Experience Analysis Through an Event Based Model Using Mereotopological Relations: From Video to Hypergraph

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Trends and Innovations in Information Systems and Technologies (WorldCIST 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1160))

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Abstract

Improving the customer experience is now strategic for insurance business. Current practices focus on subjective customer experience. In this paper, we claim that experience could be defined as a situation being processed. Thus, we propose an artifact for observation of experiences through an event based model. From video corpus, this model calculates mereotopological relations to identify “drops of experiences” as a hypergraph. Designed as a tool for marketing teams, this artifact aims to help them identify relevant customer experiences.

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Author information

Authors and Affiliations

  1. Tech-CICO Team, University of Technology of Troyes, Troyes, France

    Giles Beaudon & Eddie Soulier

  2. AI & Data, Paris, France

    Anne Gayet

Authors
  1. Giles Beaudon
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  2. Eddie Soulier
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  3. Anne Gayet
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Corresponding author

Correspondence to Giles Beaudon .

Editor information

Editors and Affiliations

  1. Departamento de Engenharia Informática, Universidade de Coimbra, Coimbra, Portugal

    Álvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

  3. FEUP, Universidade do Porto, Porto, Portugal

    Luís Paulo Reis

  4. DIMES, Università della Calabria, Arcavacata di Rende, Italy

    Sandra Costanzo

  5. Faculty of Electrical Engineering, University of Montenegro, Podgorica, Montenegro

    Irena Orovic

  6. Universidade Portucalense, Porto, Portugal

    Fernando Moreira

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Beaudon, G., Soulier, E., Gayet, A. (2020). Experience Analysis Through an Event Based Model Using Mereotopological Relations: From Video to Hypergraph. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S., Orovic, I., Moreira, F. (eds) Trends and Innovations in Information Systems and Technologies. WorldCIST 2020. Advances in Intelligent Systems and Computing, vol 1160. Springer, Cham. https://doi.org/10.1007/978-3-030-45691-7_45

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