
handle: 11858/00-001M-0000-0027-7D19-D
Although mobile devices keep getting smaller and more powerful, their interface with the user is still based on that of the regular desktop computer. This implies that interaction is usually tedious, while interrupting the user is not really desired in ubiquitous computing. We propose adding an array of hardware sensors to the system that, together with machine learning techniques, make the device aware of its context while it is being used. The goal is to make it learn the context-descriptions from its user on the spot, while minimising user-interaction and maximising reliability.
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| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 19 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
