Name
Abstract | ||
|---|---|---|
Short term studies in controlled environments have shown that user behaviour is consistent enough to predict disruptive smartphone notifications. However, in practice, user behaviour changes over time (concept drift) and individual user preferences need to be considered. There is a lack of research on which methods are best suited for predicting disruptive smartphone notifications longer-term, taking into account varying error costs. In this paper we report on a 16 week field study comparing how well different learners perform at mitigating disruptive incoming phone calls. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2628363.2628404 | Mobile HCI |
Keywords | Field | DocType |
experience sampling,miscellaneous,interruptions,smartphone,machine learning | Computer science,Experience sampling method,Concept drift,Phone,Multimedia | Conference |
Citations | PageRank | References |
7 | 0.54 | 14 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jeremiah Smith | 1 | 7 | 0.54 |
| Anna Lavygina | 2 | 11 | 1.43 |
| Jiefei Ma | 3 | 158 | 12.05 |
| Alessandra Russo | 4 | 1022 | 80.10 |
| Naranker Dulay | 5 | 1450 | 172.63 |