Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Reference21 articles.
1. Agarwal, A., Raghavan, H., Subbian, K., Melville, P., Lawrence, R. D., Gondek, D. C., & Fan, J. (2012). Learning to rank for robust question answering. In Proceedings of the 21st ACM International Conference on Information and Knowledge Management (pp. 833–842). ACM.
2. Agarwal, S., Dugar, D., & Sengupta, S. (2010). Ranking chemical structures for drug discovery: A new machine learning approach. Journal of Chemical Information and Modeling, 50(5), 716–731.
3. Aslam, J. A., Kanoulas, E., Pavlu, V., Savev, S., & Yilmaz, E. (2009). Document selection methodologies for efficient and effective learning-to-rank. In Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 468–475). ACM.
4. Cao, Z., Qin, T., Liu, T. Y., Tsai, M. F., & Li, H. (2007). Learning to rank: from pairwise approach to listwise approach. In: Proceedings of the 24th International Conference on Machine Learning (pp. 129–136). ACM.
5. Cohen, W. W., Schapire, R. E., & Singer, Y. (1999). Learning to order things. Journal of Artificial Intelligence Research, 10, 243–270.
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. An overview of sentence ordering task;International Journal of Data Science and Analytics;2024-04-25
2. Recommendation Systems: An Insight Into Current Development and Future Research Challenges;IEEE Access;2022
3. AffRankNet+: Ranking Affect Using Privileged Information;2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW);2021-09-28
4. Ranking with hamiltonian dynamics;Physica D: Nonlinear Phenomena;2020-12