Incorporating user experience into critiquing-based recommender systems: a collaborative approach based on compound critiquing-Reference-Cited by-同舟云学术

Incorporating user experience into critiquing-based recommender systems: a collaborative approach based on compound critiquing

Published:2016-10-03 Issue:5 Volume:9 Page:837-852
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Xie Haoran,Wang Debby D.,Rao Yanghui,Wong Tak-Lam,Raymond Lau Y. K.,Chen Li,Wang Fu Lee

Funder

Research Grants Council of the Hong Kong Special Administrative Region, China

Hong Kong Research Grants Council

China National Natural Science Foundation

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Internal Research Grant of the Hong Kong Institute of Education

Soft Science Research Project of Guangdong Province

Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

http://link.springer.com/article/10.1007/s13042-016-0611-2/fulltext.html

Reference50 articles.

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3. Becerra C, Gonzalez F, Gelbukh A (2011) Visualizable and explicable recommendations obtained from price estimation functions. In: Proceedings of the human decision making in recommender systems, pp 27–34

4. Bunke H, Shearer K (1998) A graph distance metric based on the maximal common subgraph. Pattern Recognit Lett 19(3):255–259

5. Burke RD, Hammond KJ, Yound BC (1997) The findme approach to assisted browsing. IEEE Intell Syst 12(4):32–40

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