V
Veljko Pejovic
Researcher at University of Ljubljana
Publications - 76
Citations - 2293
Veljko Pejovic is an academic researcher from University of Ljubljana. The author has contributed to research in topics: Mobile computing & Ubiquitous computing. The author has an hindex of 20, co-authored 69 publications receiving 1913 citations. Previous affiliations of Veljko Pejovic include University of California, Santa Barbara & University of Birmingham.
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Proceedings ArticleDOI
InterruptMe: designing intelligent prompting mechanisms for pervasive applications
Veljko Pejovic,Mirco Musolesi +1 more
TL;DR: InterruptMe, an interruption management library for Android smartphones, is designed and implemented and shows that, compared to a context-unaware approach, interruptions elicited through the library result in increased user satisfaction and shorter response times.
Proceedings ArticleDOI
My Phone and Me: Understanding People's Receptivity to Mobile Notifications
TL;DR: It is found that even a notification that contains important or useful content can cause disruption, and the substantial role of the psychological traits of the individuals on the response time and the disruption perceived from a notification is observed.
Journal ArticleDOI
Smartphones for Large-Scale Behavior Change Interventions
Neal Lathia,Veljko Pejovic,Kiran K. Rachuri,Cecilia Mascolo,Mirco Musolesi,Peter J. Rentfrow +5 more
TL;DR: The authors discuss two applications for behavioral monitoring and change and present UBhave, the first holistic platform for large-scale digital behavior change intervention.
Journal ArticleDOI
Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges
Veljko Pejovic,Mirco Musolesi +1 more
TL;DR: A survey of phenomena that mobile phones can infer and predict, and a description of machine learning techniques used for such predictions are presented, paving the way for full-fledged anticipatory mobile computing.
Proceedings ArticleDOI
Designing content-driven intelligent notification mechanisms for mobile applications
TL;DR: This paper presents a study of mobile user interruptibility with respect to notification content, its sender, and the context in which a notification is received, and shows that classifiers lead to a more accurate prediction of users' interruptibility than an alternative approach based on user-defined rules of their own interruptibility.