An Analysis of Group Recommendation Heuristics for High- and Low-Involvement Items-Reference-Cited by-同舟云学术

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An Analysis of Group Recommendation Heuristics for High- and Low-Involvement Items

Published:2017 Issue: Volume: Page:335-344
ISSN:0302-9743
Container-title:Advances in Artificial Intelligence: From Theory to Practice
language:
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Author:

Felfernig Alexander,Atas Muesluem,Tran Thi Ngoc Trang,Stettinger Martin,Erdeniz Seda Polat,Leitner Gerhard

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-60042-0_39

Reference16 articles.

1. Herlocker, J., Terveen, L., Konstan, J., Riedl, J.: Evaluating collaborative filtering recommender systems. ACM Trans. Inf. Syst. 22(1), 5–53 (2004)

2. Lecture Notes in Computer Science;A Jameson,2007

3. Jameson, A.: More than the sum of its members: challenges for group recommender systems. In: Working Conference on Advanced Visual Interfaces, AVI 2004, pp. 48–54. ACM (2004)

4. Jameson, A., Willemsen, M.C., Felfernig, A., Gemmis, M., Lops, P., Semeraro, G., Chen, L.: Human decision making and recommender systems. In: Ricci, F., Rokach, L., Shapira, B. (eds.) Recommender Systems Handbook, pp. 611–648. Springer, Boston, MA (2015). doi: 10.1007/978-1-4899-7637-6_18

5. Jannach, D., Zanker, M., Felfernig, A., Friedrich, G.: Recommender Systems: An Introduction. Cambridge University Press, Cambridge (2010)

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