You Are What You Click: Web Interaction Analysis for User Profile Detection

Autores
Loza Bonora, Leonardo Germán; Grigera, Julián; Garrido, Alejandra
Año de publicación
2025
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Evaluation of web user interaction serves various purposes like analysis and evolution of UX, but it requires significant resources. To reduce the time and cost associated with such assessments, several automated solutions have been developed to analyze interactions by capturing logs. However, many of these approaches assume that all users interact similarly, disregarding individual characteristics such as mouse and keyboard movement speeds. Additionally, they often overlook the time required for analysis. We propose that identifying a user’s interaction profile can enhance the quality of automated log analysis. To achieve this, in this proposal interactive user profiles on the web will be studied and defined. Through experimentation, we will analyze real user behavior and its relationship with these profiles. Finally, the detection of user profiles and interactive characteristics will be automated, considering key variables such as detection speed and prediction accuracy.
Materia
Ciencias de la Computación e Información
Web Interaction
User Profiling
Log Analysis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-nd/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:11746/12676

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network_name_str CIC Digital (CICBA)
spelling You Are What You Click: Web Interaction Analysis for User Profile DetectionLoza Bonora, Leonardo GermánGrigera, JuliánGarrido, AlejandraCiencias de la Computación e InformaciónWeb InteractionUser ProfilingLog AnalysisEvaluation of web user interaction serves various purposes like analysis and evolution of UX, but it requires significant resources. To reduce the time and cost associated with such assessments, several automated solutions have been developed to analyze interactions by capturing logs. However, many of these approaches assume that all users interact similarly, disregarding individual characteristics such as mouse and keyboard movement speeds. Additionally, they often overlook the time required for analysis. We propose that identifying a user’s interaction profile can enhance the quality of automated log analysis. To achieve this, in this proposal interactive user profiles on the web will be studied and defined. Through experimentation, we will analyze real user behavior and its relationship with these profiles. Finally, the detection of user profiles and interactive characteristics will be automated, considering key variables such as detection speed and prediction accuracy.2025info: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/11746/12676enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2026-03-26T11:18:36Zoai:digital.cic.gba.gob.ar:11746/12676Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412026-03-26 11:18:36.96CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse
dc.title.none.fl_str_mv You Are What You Click: Web Interaction Analysis for User Profile Detection
title You Are What You Click: Web Interaction Analysis for User Profile Detection
spellingShingle You Are What You Click: Web Interaction Analysis for User Profile Detection
Loza Bonora, Leonardo Germán
Ciencias de la Computación e Información
Web Interaction
User Profiling
Log Analysis
title_short You Are What You Click: Web Interaction Analysis for User Profile Detection
title_full You Are What You Click: Web Interaction Analysis for User Profile Detection
title_fullStr You Are What You Click: Web Interaction Analysis for User Profile Detection
title_full_unstemmed You Are What You Click: Web Interaction Analysis for User Profile Detection
title_sort You Are What You Click: Web Interaction Analysis for User Profile Detection
dc.creator.none.fl_str_mv Loza Bonora, Leonardo Germán
Grigera, Julián
Garrido, Alejandra
author Loza Bonora, Leonardo Germán
author_facet Loza Bonora, Leonardo Germán
Grigera, Julián
Garrido, Alejandra
author_role author
author2 Grigera, Julián
Garrido, Alejandra
author2_role author
author
dc.subject.none.fl_str_mv Ciencias de la Computación e Información
Web Interaction
User Profiling
Log Analysis
topic Ciencias de la Computación e Información
Web Interaction
User Profiling
Log Analysis
dc.description.none.fl_txt_mv Evaluation of web user interaction serves various purposes like analysis and evolution of UX, but it requires significant resources. To reduce the time and cost associated with such assessments, several automated solutions have been developed to analyze interactions by capturing logs. However, many of these approaches assume that all users interact similarly, disregarding individual characteristics such as mouse and keyboard movement speeds. Additionally, they often overlook the time required for analysis. We propose that identifying a user’s interaction profile can enhance the quality of automated log analysis. To achieve this, in this proposal interactive user profiles on the web will be studied and defined. Through experimentation, we will analyze real user behavior and its relationship with these profiles. Finally, the detection of user profiles and interactive characteristics will be automated, considering key variables such as detection speed and prediction accuracy.
description Evaluation of web user interaction serves various purposes like analysis and evolution of UX, but it requires significant resources. To reduce the time and cost associated with such assessments, several automated solutions have been developed to analyze interactions by capturing logs. However, many of these approaches assume that all users interact similarly, disregarding individual characteristics such as mouse and keyboard movement speeds. Additionally, they often overlook the time required for analysis. We propose that identifying a user’s interaction profile can enhance the quality of automated log analysis. To achieve this, in this proposal interactive user profiles on the web will be studied and defined. Through experimentation, we will analyze real user behavior and its relationship with these profiles. Finally, the detection of user profiles and interactive characteristics will be automated, considering key variables such as detection speed and prediction accuracy.
publishDate 2025
dc.date.none.fl_str_mv 2025
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info:eu-repo/semantics/publishedVersion
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dc.identifier.none.fl_str_mv https://digital.cic.gba.gob.ar/handle/11746/12676
url https://digital.cic.gba.gob.ar/handle/11746/12676
dc.language.none.fl_str_mv eng
language eng
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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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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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