Models of attention in computing and communication
By Eric Horvitz, Carl Myers Kadie, Tim Paek, D. Hovel. Communications of the ACM, 2003
370 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems and Management
View Paper: https://www.semanticscholar.org/paper/11e30696a7709dee619e5a4f051aca6d5b577cca
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Bodo Urban
- Christian Peter
- Johnson Apacible
- Yufei Ma
- Xiansheng Hua
- Eric Horvitz
- Joyce Ho
- Stephen S. Intille
In Computer Vision and Pattern Recognition
In Information Systems and Management
- Joyce Ho
- Stephen S. Intille
- Eric Horvitz
- Johnson Apacible
- Bodo Urban
- Christian Peter
- Shamsi T. Iqbal
- Brian P. Bailey
Citations in the corpus
- Emotion in Human-Computer Interaction (2012, methodology): “There exist several methods to attract the user’s attention, but only less objective and technical supported methods to identify the focus of attention (see [49]) or recognize the impact of these methods on the user.”
- Synchronous gestures for multiple persons and computers (2003, background): “The Notification Platform [ 19 ] coordinates sensor information (mouse and keyboard activity, microphones, and cameras) from multiple devices to optimize delivery of messages.”
- Learning and reasoning about interruption (2003, methodology): “Following a review of prior work on techniques for deliberating about the cost of interruption associated with notifications, we introduce methods for learning models from data that can be used to compute the expected cost of interruption for a user.”
- A generic framework of user attention model and its application in video summarization (2005, background): “significant implications for how we design computat ional system and interfaces [ 22 ].”
- Using context-aware computing to reduce the perceived burden of interruptions from mobile devices (2005, background): “Modality of interruption The medium of delivery, or choice of interface [32, 1, 27, 14 ] Frequency of interruption The rate at which interruptions are occurring [27] Task efficiency rate The time it takes to comprehend the interruption task and the expected length of the task [9, 27, 31]”