To Be or Not to Be Aware: Reducing Interruptions in Pervasive Awareness Systems

Petersen, Sobah Abbas; Cassens, Jörg; Kofod-Petersen, Anders; Divitini, Monica

doi:10.1109/ubicomm.2008.35

Cited by 9 publications

(4 citation statements)

References 25 publications

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“…Broadly speaking, reviews and analysis of interruptibility studies have involved two distinct approaches. On the one hand, interruptibility has been encompassed within the concepts and visions of wider attention-aware systems [45,49,40,54]. On the other hand, works have evaluated specific conventions relevant to interruptibility, such as the contextual features adopted [19]; whether to use experience sampling methods (ESM) [33] ; or human labelling by a third party [3].…”

Section: Objective and Organisation Of The Papermentioning

confidence: 99%

Interruptibility prediction for ubiquitous systems

Turner

Allen

Whitaker

2015

Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing

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When should a machine attempt to communicate with a user? This is a historical problem that has been studied since the rise of personal computing. More recently, the emergence of pervasive technologies such as the smartphone have extended the problem to be ever-present in our daily lives, opening up new opportunities for context awareness through data collection and reasoning. Complementary to this there has been increasing interest in techniques to intelligently synchronise interruptions with human behaviour and cognition. However, it is increasingly challenging to categorise new developments, which are often scenario specific or scope a problem with particular unique features. In this paper we present a metaanalysis of this area, decomposing and comparing historical and recent works that seek to understand and predict how users will perceive and respond to interruptions. In doing so we identify research gaps, questions and opportunities that characterise this important emerging field for pervasive technology.

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Section: Objective and Organisation Of The Papermentioning

confidence: 99%

Interruptibility prediction for ubiquitous systems

Turner

Allen

Whitaker

2015

Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing

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“…Whether an interruption is beneficial or harmful depends on the contexts the user is surrounded by. Numerous researchers, focused on modeling context, also paid attention on how they can specify the contexts that play significant role in understanding unwanted disruptions [4,9,13,18,20,29,27]. Further, a number of researchers also proposed models or systems that reduce the cost of interruption [2,4,6,8,16,28].…”

Section: Related Workmentioning

confidence: 99%

A context-aware cost of interruption model for mobile devices

Zulkernain

Madiraju

Ahamed

2011

2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops)

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Unwanted and untimely interruptions have been a major cause in the loss of productivity in recent years as they are mostly detrimental to the immediate task at hand. Multiple approaches have been proposed to address the problem of interruption by calculating cost of interruption. The cost of interruption (COI) gives as a measure the probabilistic value of harmfulness of an inopportune interruption. Bayesian Inference stands atop among the models that have been applied to calculate this COI. However Bayesian inference based models suffer from not being able to model context accurately in situations where priori, conditional probabilities and uncertainties exist while utilizing context information. Hence, this paper introduces Dempster-Shafer Theory of Evidence to model COI. Along the way, we also identify different contexts necessary for interruption management applications. We also show an illustrative example of a mobile interruption management application where the Dempster-Shafer theory is used to get a better measurement of whether to interrupt or not.

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“…[15]) found negative [3,6,10], and (c) technological solutions, which can help prevent unwanted interruptions from taking place, as well as help users recover from interruptions if they do take place (e.g., [1,7,12]). …”

Section: Introductionmentioning

confidence: 99%

“…[12,13,14]) the social dimension of interruptions has been neglected. As we argue in a previous paper [8], the "ripple effect" of interruptions, that is, indirect consequences of interruptions within the social context of an activity, is underrepresented in existing research.…”

Section: Introductionmentioning

confidence: 99%

Interrupting or not

Harr

Kaptelinin

2012

Proceedings of the 7th Nordic Conference on Human-Computer Interaction: Making Sense Through Design

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In recent decades technology-induced interruptions emerged as a key object of study in HCI and CSCW research, but until recently the social dimension of interruptions has been relatively neglected. The focus of existing research on interruptions has been mostly on their direct effects on the persons whose activities are interrupted. Arguably, however, it is also necessary to take into account the "ripple effect" of interruptions, that is, indirect consequences of interruptions within the social context of an activity, to properly understand interrupting behavior and provide advanced technological support for handling interruptions. This paper reports an empirical study, in which we examine a set of facets of the social context of interruptions, which we identified in a previous conceptual analysis. The results suggest that people do take into account various facets of the social context when making decisions about whether or not it is appropriate to interrupt another person.

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To Be or Not to Be Aware: Reducing Interruptions in Pervasive Awareness Systems

Cited by 9 publications

References 25 publications

Interruptibility prediction for ubiquitous systems

Interruptibility prediction for ubiquitous systems

A context-aware cost of interruption model for mobile devices

Interrupting or not

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