@inproceedings{DoetterlBrunsDunkel2017,
  author    = {Jeremias D{\"o}tterl and Ralf Bruns and J{\"u}rgen Dunkel},
  title     = {Incorporating Situation Awareness into Recommender Systems},
  series = {Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
  isbn      = {978-989-758-248-6},
  doi       = {10.25968/opus-1742},
  url       = {http://nbn-resolving.de/urn:nbn:de:bsz:960-opus4-17424},
  pages     = {676 -- 683},
  year      = {2017},
  abstract  = {Nowadays, smartphones and sensor devices can provide a variety of information about a user’s current situation. So far, many recommender systems neglect this kind of information and thus cannot provide situationspecific recommendations. Situation-aware recommender systems adapt to changes in the user’s environment and therefore are able to offer recommendations that are more appropriate for the current situation. In this paper, we present a software architecture that enables situation awareness for arbitrary recommendation techniques. The proposed system considers both (semi-)static user profiles and volatile situational knowledge to obtain meaningful recommendations. Furthermore, the implementation of the architecture in a museum of natural history is presented, which uses Complex Event Processing to achieve situation awareness.},
  language  = {en}
}