A multi-aspect user-interest model based on sentiment analysis and uncertainty theory for recommender systems-Reference-Cited by-同舟云学术

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A multi-aspect user-interest model based on sentiment analysis and uncertainty theory for recommender systems

Published:2018-09-29 Issue:4 Volume:20 Page:857-882
ISSN:1389-5753
Container-title:Electronic Commerce Research
language:en
Short-container-title:Electron Commer Res

Author:

Sun Lihua,Guo Junpeng,Zhu Yanlin

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Human-Computer Interaction,Economics, Econometrics and Finance (miscellaneous)

Link

http://link.springer.com/content/pdf/10.1007/s10660-018-9319-6.pdf

Reference49 articles.

1. Chen, Y.-C., Shang, R.-A., & Kao, C.-Y. (2009). The effects of information overload on consumers’ subjective state towards buying decision in the internet shopping environment. Electronic Commerce Research and Applications, 8(1), 48–58.

2. Bobadilla, J., Ortega, F., Hernando, A., & Gutiérrez, A. (2013). Recommender systems survey. Knowledge-Based Systems, 46, 109–132.

3. Aljukhadar, M., Senecal, S., & Daoust, C.-E. (2012). Using recommendation agents to cope with information overload. International Journal of Electronic Commerce, 17(2), 41–70.

4. Lu, J., Wu, D., Mao, M., Wang, W., & Zhang, G. (2015). Recommender system application developments: A survey. Decision Support Systems, 74, 12–32.

5. Adomavicius, G., & Tuzhilin, A. (2005). Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering, 17(6), 734–749.

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