Name
Abstract | ||
|---|---|---|
Home entertainment systems feature in a variety of usage scenarios with one or more simultaneous users, for whom the complexity of choosing media to consume has increased rapidly over the last decade. Usersu0027 decision processes are complex and highly influenced by contextual settings, but data supporting the development and evaluation of context-aware recommender systems are scarce. In this paper we present a dataset of self-reported TV consumption enriched with contextual information of viewing situations. We show how choice of genre associates with, among others, the number of present users and usersu0027 attention levels. Furthermore, we evaluate the performance of predicting chosen genres given different configurations of contextual information, and compare the results to contextless predictions. The results suggest that including contextual features in the prediction cause notable improvements, and both temporal and social context show significant contributions. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/tmm.2019.2944214 | IEEE Transactions on Multimedia |
Field | DocType | Volume |
Recommender system,Social environment,Contextual information,Information retrieval,Computer science,Home entertainment,Decision process | Journal | abs/1808.00337 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Miklas S Kristoffersen | 1 | 12 | 3.06 |
| Sven Ewan Shepstone | 2 | 18 | 3.69 |
| Zheng-Hua Tan | 3 | 457 | 60.32 |