Characterising Players of a Cube Puzzle Game with a Two-level Bag of Words
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Otros documentos de la autoría: Anadón, Xavier; Sanahuja, Pablo; Traver, V. Javier; Lopez, Angeles; Ribelles, Jose
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Título
Characterising Players of a Cube Puzzle Game with a Two-level Bag of WordsFecha de publicación
2021-06Editor
Association for Computing Machinery (ACM)ISBN
978-1-4503-8367-7Cita bibliográfica
ANADÓN, Xavier, et al. Characterising Players of a Cube Puzzle Game with a Two-level Bag of Words. In: Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization. 2021. p. 47-53.Tipo de documento
info:eu-repo/semantics/conferenceObjectVersión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
This work explores an unsupervised approach for modelling players
of a 2D cube puzzle game with the ultimate goal of customising the
game for particular players based solely on their interaction data.
To that end, ... [+]
This work explores an unsupervised approach for modelling players
of a 2D cube puzzle game with the ultimate goal of customising the
game for particular players based solely on their interaction data.
To that end, user interactions when solving puzzles are coded as
images. Then, a feature embedding is learned for each puzzle with
a convolutional network trained to regress the players’ comple tion effort in terms of time and number of clicks. Next, the known
bag-of-words technique is used at two levels. First, sets of puzzles
are represented using the puzzle feature embeddings as the input
space. Second, the resulting first-level histograms are used as input
space for characterising players. As a result, new players can be
characterised in terms of the resulting second-level histograms.
Preliminary results indicate that the approach is effective for char acterising players in terms of performance. It is also tentatively
observed that other personal perceptions and preferences, beyond
performance, are somehow implicitly captured from behavioural
data. [-]
Descripción
Ponencia presentada en UMAP '21: Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization, Utrecht (Netherlands), June 21 - 25, 2021
Publicado en
Judith Masthoff, Eelco Herder, Nava Tintarev, Marko Tkalčič (Eds.). UMAP '21: Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization, Association for Computing Machinery, 2021, ISBN 978-1-4503-8367-7Derechos de acceso
© 2021 Copyright held by the owner/author(s
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