Preface to the special issue on context-aware recommender systems

User Modeling and User-Adapted Interaction

Volumn 24, Issue 1-2, 2014, Pages 1-5

  Adomavicius, Gediminas ^a   Jannach, Dietmar ^b  

^a UNIVERSITY OF MINNESOTA   (United States)

^b TU DORTMUND UNIVERSITY   (Germany)

Author keywords

Collaborative filtering; Context awareness; Recommender systems

Indexed keywords

EID: 84894026563     PISSN: 09241868     EISSN: 15731391     Source Type: Journal    
DOI: 10.1007/s11257-013-9139-2     Document Type: Review

References (7)

1. Adomavicius, G.; Mobasher, B.; Ricci, F.; Tuzhilin, A.: Context-aware recommender systems. AI Mag. 32(3), 67-80 (2011)
2. Adomavicius, G.; Tuzhilin, A.: Context-aware recommender systems. In: Ricci, F.; Rokach, L.; Shapira, B.; Kantor, P.B. (eds.) Recommender Systems Handbook, pp. 217-253. Springer, New York (2011)
3. Baltrunas, L.; Ricci, F.: Experimental evaluation of context-dependent collaborative filtering using item splitting. User Model User-Adap. Inter. (2014). doi: 10.1007/S11257-012-9137-9
4. Campos, P.G.; Díez, F.; Cantador, I.: Time-aware recommender systems: A comprehensive survey and analysis of existing evaluation protocols. User Modeling and User Model User-Adap. Inter. (2014). doi: 10.1007/S11257-012- 9136-x
5. Hussein, T.; Linder, T.; Gaulke, W.; Ziegler, J.: Hybreed: A software framework for developing context-aware hybrid recommender systems. User Modeling and User Model User-Adap. Inter. (2014). doi: 10.1007/S11257-012-9134-z
6. Jannach, D.; Zanker, M.; Felfernig, A.; Friedrich, G.: Recommender Systems: An Introduction. Cambridge University Press, Cambridge (2010)
7. Panniello, U.; Tuzhilin, A.; Gorgoglione, M.: Comparing context-aware recommender systems in terms of accuracy and diversity: Which contextual modeling, pre-filtering and post-filtering methods perform the best. User Model User-Adap. Inter. (2014). doi: 10.1007/S11257-012-9135-y