User behavior sequence modeling to optimize ranking mechanism for e-commerce search-Reference-Cited by-同舟云学术

User behavior sequence modeling to optimize ranking mechanism for e-commerce search

Published:2017 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 3rd International Conference on Communication and Information Processing - ICCIP '17
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Author:

Huo Chengfu¹,Zhao Yujiao¹,Ren Weijun¹

Affiliation:

1. Alibaba Group, Hangzhou City, China

Publisher

ACM Press

Reference12 articles.

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2. Cheng, H., and Cantu-Paz, E. 2010. Personalized click prediction in sponsored search. In Proceedings of the third ACM International Conference on Web Search and Data Mining (Feb. 04--06, 2010). New York, USA

3. Huang, P. S., He X., Gao, J., Deng L., Acero, A., and Heck, H. 2013. Learning deep structured semantic models for web search using clickthrough data. In Proceedings of the 22nd ACM International Conference on Information & Knowledge Management (Oct. 27-Nov. 01, 2013). San Francisco, California, USA, 2333--2338.

4. Song, Y., Wang, H., and He, X. 2014. Adapting deep ranknet for personalized search. In Proceedings of the 7th ACM International Conference on Web Search and Data Mining (Feb. 24--28, 2014). New York, USA, 83--92.

5. McMahan, H. B., Holt, G., Sculley, D., Young, M., Ebner, D., et al. 2013. Ad click prediction: a view from trenches. In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (Aug. 11--14, 2013). Chicago, USA.

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