title: User clustering in smartphone applications.
abstract: In the context of mobile health applications usability is a crucial factor to achieve user acceptance. The successful user interface (UI) design requires a deep understanding of the needs and requirements of the targeted audience. This paper explores the application of the K-Means algorithm on smartphone usage data in order to offer Human Computer Interaction (HCI) specialists a better insight into their user group. Two different feature space representations are introduced and used to identify persona like stereotypes in a real world data set, which was obtained from a public available smartphone application.
authors.affiliation: Faculdade de Engenharia da Universidade do Porto, Porto, Portugal. pro11010@fe.up.pt
authors.forename: Klaus
authors.initials: K
authors.lastname: Schaefers
authors.forename: David
authors.initials: D
authors.lastname: Ribeiro
mesh_terms: D040421:Cell Phone / Q000706:statistics & numerical data*; D034201:Computers, Handheld / Q000706:statistics & numerical data*; D057225:Data Mining / Q000379:methods*; D003936:Diagnosis, Computer-Assisted / Q000706:statistics & numerical data; D008328:Man-Machine Systems; D018670:Monitoring, Ambulatory / Q000706:statistics & numerical data*; D017216:Telemedicine / Q000295:instrumentation*; D013686:Telemetry / Q000706:statistics & numerical data*