Author: Markus Zanker
Publications
Co-authors
Productive Colleagues
Publications
Zanker, Markus, Ricci, Francesco, Jannach, Dietmar, Terveen, Loren (2010): Measuring the impact of personalization and recommendation on user behaviour. In International Journal of Human-Computer Studies, 68 (8) pp. 469-471. https://www.sciencedirect.com/science/article/B6WGR-503R04G-2/2/e113dff4944ae419d9be112da74975b7
Ardissono, Liliana, Felfernig, Alexander, Friedrich, Gerhard, Jannach, Dietmar, Schäfer, Ralph, Zanker, Markus (2001): Intelligent Interfaces for Distributed Web-Based Product and Service Configuration. In: Zhong, Ning, Yao, Yiyu, Liu, Jiming, Ohsuga, Setsuo (eds.) Web Intelligence Research and Development - First Asia-Pacific Conference - WI 2001 October 23-26, 2001, Maebashi City, Japan. pp. 184-188. https://link.springer.de/link/service/series/0558/bibs/2198/21980184.htm
Felfernig, Alexander, Zanker, Markus (2000): Diagrammatic Acquisition of Functional Knowledge for Product Configuration Systems with th. In: Anderson, Michael, Cheng, Peter C-H., Haarslev, Volker (eds.) Diagrams 2000 - Theory and Application of Diagrams - First International Conference September 1-3, 2000, Edinburgh, Scotland, UK. pp. 361-375. https://link.springer.de/link/service/series/0558/bibs/1889/18890361.htm
Kattamuri, Kishore, Silaghi, Marius-Calin, Kaner, Cem, Stansifer, Ryan, Zanker, Markus (2005): Supporting debates over citizen initiatives. In: Delcambre, Lois M. L., Giuliano, Genevieve (eds.) DG.O 2005 - Proceedings of the 2005 National Conference on Digital Government Research May 15-18, 2005, Atlanta, Georgia, USA. pp. 279-280. https://doi.acm.org/10.1145/1065226.1065321
Zanker, Markus (2008): A collaborative constraint-based meta-level recommender. In: Proceedings of the 2008 ACM Conference on Recommender Systems , 2008, . pp. 139-146. https://dx.doi.org/10.1145/1454008.1454032
Zanker, Markus (2012): The influence of knowledgeable explanations on users' perception of a recommender system. In: Proceedings of the 2012 ACM Conference on Recommender Systems , 2012, . pp. 269-272. https://dx.doi.org/10.1145/2365952.2366011