The Importance of Context When Recommending TV Content: Dataset and Algorithms

Miklas Strøm Kristoffersen, Sven Ewan Shepstone, Zheng-Hua Tan

Research output: Contribution to journalJournal articleResearchpeer-review

3 Citations (Scopus)
13 Downloads (Pure)


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. Users' 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 users' 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.

Original languageEnglish
Article number8851276
JournalI E E E Transactions on Multimedia
Issue number6
Pages (from-to)1531-1541
Number of pages11
Publication statusPublished - 2020


  • Context awareness
  • TV
  • data collection
  • recommender systems


Dive into the research topics of 'The Importance of Context When Recommending TV Content: Dataset and Algorithms'. Together they form a unique fingerprint.

Cite this