Author:
Qin Tao,Liu Tie-Yan,Li Hang
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Information Systems
Reference31 articles.
1. Burges, C., Shaked, T., Renshaw, E., Lazier, A., Deeds, M., Hamilton, N., et al. (2005). Learning to rank using gradient descent. In ICML ’05: Proceedings of the 22nd international conference on Machine learning (pp. 89–96). New York, NY, USA: ACM Press.
2. Cao, Z., Qin, T., Liu, T.-Y., Tsai, M.-F., & Li, H. (2007). Learning to rank: From pairwise approach to listwise approach. In ICML ’07: Proceedings of the 24th international conference on Machine learning (pp. 129–136). New York, NY, USA: ACM Press.
3. Chakrabarti, S., Khanna, R., Sawant, U., & Bhattacharyya, C. (2008). Structured learning for non-smooth ranking losses. In KDD ’08: Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 88–96). New York, NY, USA: ACM.
4. Chapelle, O., Le, Q., & Smola, A. (2007). Large margin optimization of ranking measures. In NIPS2007 workshop on machine learning for Web search.
5. Duh, K., & Kirchhoff, K. (2008). Learning to rank with partially-labeled data. In SIGIR ’08: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (pp. 251–258). New York, NY, USA: ACM.
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