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Emojinating: Evolving Emoji Blends

  • Conference paper
Book cover Computational Intelligence in Music, Sound, Art and Design (EvoMUSART 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11453))

Abstract

Graphic designers visually represent concepts in several of their daily tasks, such as in icon design. Computational systems can be of help in such tasks by stimulating creativity. However, current computational approaches to concept visual representation lack in effectiveness in promoting the exploration of the space of possible solutions. In this paper, we present an evolutionary approach that combines a standard Evolutionary Algorithm with a method inspired by Estimation of Distribution Algorithms to evolve emoji blends to represent user-introduced concepts. The quality of the developed approach is assessed using two separate user-studies. In comparison to previous approaches, our evolutionary system is able to better explore the search space, obtaining solutions of higher quality in terms of concept representativeness.

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Notes

  1. 1.

    emojisaurus.com, retrieved 2019.

  2. 2.

    quickdraw.withgoogle.com, retrieved 2019.

  3. 3.

    forbes.com/sites/jaysondemers/2017/06/01/could-emoji-searches-and-emoji-seo-become-a-trend/, retrieved 2018.

  4. 4.

    macrumors.com/how-to/ios-10-messages-emoji/, retrieved 2018.

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Acknowledgments

João M. Cunha is partially funded by Fundação para a Ciência e Tecnologia (FCT), Portugal, under the grant SFRH/BD/120905/2016; and is based upon work from COST Action CA15140: ImAppNIO, supported by COST (European Cooperation in Science and Technology): www.cost.eu. This work includes data from ConceptNet 5, which was compiled by the Commonsense Computing Initiative and is freely available under the Creative Commons Attribution-ShareAlike license (CC BY SA 4.0) from conceptnet.io.

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Authors and Affiliations

  1. CISUC, Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal

    João M. Cunha, Nuno Lourenço, João Correia, Pedro Martins & Penousal Machado

Authors
  1. João M. Cunha
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  2. Nuno Lourenço
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  3. João Correia
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  4. Pedro Martins
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  5. Penousal Machado
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Corresponding author

Correspondence to João M. Cunha .

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Editors and Affiliations

  1. Aston University, Birmingham, UK

    Anikó Ekárt

  2. University of Malta, Msida, Malta

    Antonios Liapis

  3. University of A Coruña, A Coruña, Spain

    María Luz Castro Pena

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Cunha, J.M., Lourenço, N., Correia, J., Martins, P., Machado, P. (2019). Emojinating: Evolving Emoji Blends. In: Ekárt, A., Liapis, A., Castro Pena, M.L. (eds) Computational Intelligence in Music, Sound, Art and Design. EvoMUSART 2019. Lecture Notes in Computer Science(), vol 11453. Springer, Cham. https://doi.org/10.1007/978-3-030-16667-0_8

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  • DOI: https://doi.org/10.1007/978-3-030-16667-0_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-16666-3

  • Online ISBN: 978-3-030-16667-0

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