Anomalous behavior identification using statistical analysis of large scale user interaction data

Abstract: The challenge of identifying usability problems in interactive applications has been dealt with by companies for decades, but the amount of issues found in production systems illustrates how far we are from a widely usable solution. The integration of statistical analysis of large scale us...

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Detalles Bibliográficos
Autores principales: Urbano, Paulo, Cruz, Rodrigo, Dallegrave, Támara
Otros Autores: Interaction Design Association ; Asociación de Profesionales en Experiencia de Usuario ; Internet Society ; Universidad Católica Argentina
Formato: Documento de conferencia
Lenguaje:Portugués
Publicado: 2019
Materias:
USABILIDAD
ANALISIS ESTADISTICO
USUARIOS
INTERACCION
TECNOLOGIA DE LA INFORMACION
COMUNICACION
ISA14
Acceso en línea:https://repositorio.uca.edu.ar/handle/123456789/7970
Aporte de:
Repositorio Institucional de la Universidad Católica Argentina (UCA) de Universidad Católica Argentina
id I33-R139123456789-7970
record_format dspace
institution Universidad Católica Argentina
institution_str I-33
repository_str R-139
collection Repositorio Institucional de la Universidad Católica Argentina (UCA)
language Portugués
topic USABILIDAD
ANALISIS ESTADISTICO
USUARIOS
INTERACCION
TECNOLOGIA DE LA INFORMACION
COMUNICACION
ISA14
spellingShingle USABILIDAD
ANALISIS ESTADISTICO
USUARIOS
INTERACCION
TECNOLOGIA DE LA INFORMACION
COMUNICACION
ISA14
Urbano, Paulo
Cruz, Rodrigo
Dallegrave, Támara
Anomalous behavior identification using statistical analysis of large scale user interaction data
topic_facet USABILIDAD
ANALISIS ESTADISTICO
USUARIOS
INTERACCION
TECNOLOGIA DE LA INFORMACION
COMUNICACION
ISA14
description Abstract: The challenge of identifying usability problems in interactive applications has been dealt with by companies for decades, but the amount of issues found in production systems illustrates how far we are from a widely usable solution. The integration of statistical analysis of large scale user interaction data into a user centered design process, presented by the authors in an earlier work [1], can significantly improve the chance of identifying usability problems in certain classes of applications. In this article, an expansion of the approach is proposed, leveraging the concept of ‘task’ as defined in the ISO 9241-11 [2] to create the basis for the automatic identification of anomalous interaction behavior. Here, ‘anomalous’ is understood as any statistically significant deviation from the expected interaction behavior, as defined in the implemented information architecture and navigation flow, or from the most often observed interaction pattern. With that, we argue, a relevant new tool to support the process of usability evaluation is created, uncovering interaction patterns not easily identifiable by other means
author2 Interaction Design Association ; Asociación de Profesionales en Experiencia de Usuario ; Internet Society ; Universidad Católica Argentina
author_facet Interaction Design Association ; Asociación de Profesionales en Experiencia de Usuario ; Internet Society ; Universidad Católica Argentina
Urbano, Paulo
Cruz, Rodrigo
Dallegrave, Támara
format Documento de conferencia
author Urbano, Paulo
Cruz, Rodrigo
Dallegrave, Támara
author_sort Urbano, Paulo
title Anomalous behavior identification using statistical analysis of large scale user interaction data
title_short Anomalous behavior identification using statistical analysis of large scale user interaction data
title_full Anomalous behavior identification using statistical analysis of large scale user interaction data
title_fullStr Anomalous behavior identification using statistical analysis of large scale user interaction data
title_full_unstemmed Anomalous behavior identification using statistical analysis of large scale user interaction data
title_sort anomalous behavior identification using statistical analysis of large scale user interaction data
publishDate 2019
url https://repositorio.uca.edu.ar/handle/123456789/7970
work_keys_str_mv AT urbanopaulo anomalousbehavioridentificationusingstatisticalanalysisoflargescaleuserinteractiondata
AT cruzrodrigo anomalousbehavioridentificationusingstatisticalanalysisoflargescaleuserinteractiondata
AT dallegravetamara anomalousbehavioridentificationusingstatisticalanalysisoflargescaleuserinteractiondata
bdutipo_str Repositorios
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