Relevance of non-activity representation in traveling user behavior profiling for adaptive gamification

Autores
Dalponte Ayastuy, María; Torres, Diego
Año de publicación
2021
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Collaborative location collecting systems (CLCS) are collaborative systems where users collects location-based data. When these systems are gamified and aim to adapt the game elements to each user, it may require a user traveling behavior profile. This work presents two approaches of traveling user behavior profiling: a raw series built up with categorical data that describes the user’s activity in a period, and a timed series that is an enhanced version of the first that includes a representation of the non-activity time frames. The profiling of user traveling behavior can be used in adaptive gamification strategies. The approach is evaluated over a behavioral atoms dataset based on a year of Foursquare check-ins. The results showed that both approaches reflex different aspects of traveling user behavior, and also both could be used in a complementary manner.
Materia
Ciencias de la Computación e Información
User profiling
Adaptive gamification
Collaborative location collecting systems
Dynamic time warping clustering
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
CIC Digital (CICBA)
Institución
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
OAI Identificador
oai:digital.cic.gba.gob.ar:11746/11545
Acceder
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network_acronym_str CICBA
repository_id_str 9441
network_name_str CIC Digital (CICBA)
spelling Relevance of non-activity representation in traveling user behavior profiling for adaptive gamificationDalponte Ayastuy, MaríaTorres, DiegoCiencias de la Computación e InformaciónUser profilingAdaptive gamificationCollaborative location collecting systemsDynamic time warping clusteringCollaborative location collecting systems (CLCS) are collaborative systems where users collects location-based data. When these systems are gamified and aim to adapt the game elements to each user, it may require a user traveling behavior profile. This work presents two approaches of traveling user behavior profiling: a raw series built up with categorical data that describes the user’s activity in a period, and a timed series that is an enhanced version of the first that includes a representation of the non-activity time frames. The profiling of user traveling behavior can be used in adaptive gamification strategies. The approach is evaluated over a behavioral atoms dataset based on a year of Foursquare check-ins. The results showed that both approaches reflex different aspects of traveling user behavior, and also both could be used in a complementary manner.2021info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/11545enginfo:eu-repo/semantics/altIdentifier/doi/10.1145/3471391.3471431info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-09-29T13:40:08Zoai:digital.cic.gba.gob.ar:11746/11545Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-09-29 13:40:08.538CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse
dc.title.none.fl_str_mv Relevance of non-activity representation in traveling user behavior profiling for adaptive gamification
title Relevance of non-activity representation in traveling user behavior profiling for adaptive gamification
spellingShingle Relevance of non-activity representation in traveling user behavior profiling for adaptive gamification
Dalponte Ayastuy, María
Ciencias de la Computación e Información
User profiling
Adaptive gamification
Collaborative location collecting systems
Dynamic time warping clustering
title_short Relevance of non-activity representation in traveling user behavior profiling for adaptive gamification
title_full Relevance of non-activity representation in traveling user behavior profiling for adaptive gamification
title_fullStr Relevance of non-activity representation in traveling user behavior profiling for adaptive gamification
title_full_unstemmed Relevance of non-activity representation in traveling user behavior profiling for adaptive gamification
title_sort Relevance of non-activity representation in traveling user behavior profiling for adaptive gamification
dc.creator.none.fl_str_mv Dalponte Ayastuy, María
Torres, Diego
author Dalponte Ayastuy, María
author_facet Dalponte Ayastuy, María
Torres, Diego
author_role author
author2 Torres, Diego
author2_role author
dc.subject.none.fl_str_mv Ciencias de la Computación e Información
User profiling
Adaptive gamification
Collaborative location collecting systems
Dynamic time warping clustering
topic Ciencias de la Computación e Información
User profiling
Adaptive gamification
Collaborative location collecting systems
Dynamic time warping clustering
dc.description.none.fl_txt_mv Collaborative location collecting systems (CLCS) are collaborative systems where users collects location-based data. When these systems are gamified and aim to adapt the game elements to each user, it may require a user traveling behavior profile. This work presents two approaches of traveling user behavior profiling: a raw series built up with categorical data that describes the user’s activity in a period, and a timed series that is an enhanced version of the first that includes a representation of the non-activity time frames. The profiling of user traveling behavior can be used in adaptive gamification strategies. The approach is evaluated over a behavioral atoms dataset based on a year of Foursquare check-ins. The results showed that both approaches reflex different aspects of traveling user behavior, and also both could be used in a complementary manner.
description Collaborative location collecting systems (CLCS) are collaborative systems where users collects location-based data. When these systems are gamified and aim to adapt the game elements to each user, it may require a user traveling behavior profile. This work presents two approaches of traveling user behavior profiling: a raw series built up with categorical data that describes the user’s activity in a period, and a timed series that is an enhanced version of the first that includes a representation of the non-activity time frames. The profiling of user traveling behavior can be used in adaptive gamification strategies. The approach is evaluated over a behavioral atoms dataset based on a year of Foursquare check-ins. The results showed that both approaches reflex different aspects of traveling user behavior, and also both could be used in a complementary manner.
publishDate 2021
dc.date.none.fl_str_mv 2021
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info:eu-repo/semantics/publishedVersion
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info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
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dc.identifier.none.fl_str_mv https://digital.cic.gba.gob.ar/handle/11746/11545
url https://digital.cic.gba.gob.ar/handle/11746/11545
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1145/3471391.3471431
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:CIC Digital (CICBA)
instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
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reponame_str CIC Digital (CICBA)
collection CIC Digital (CICBA)
instname_str Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
instacron_str CICBA
institution CICBA
repository.name.fl_str_mv CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
repository.mail.fl_str_mv marisa.degiusti@sedici.unlp.edu.ar
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