Learning to rank query suggestions for adhoc and diversity search

The whens and hows of learning to rank f

The whens and hows of learning to rank for web search

✍ Macdonald, Craig; Santos, Rodrygo L. T.; Ounis, Iadh 📂 Article 📅 2012 🏛 Springer Netherlands 🌐 English ⚖ 952 KB

[IEEE 2009 International Conference on M

[IEEE 2009 International Conference on Machine Learning and Cybernetics (ICMLC) - Baoding, China (2009.07.12-2009.07.15)] 2009 International Conference on Machine Learning and Cybernetics - A query-level active sampling approach for learning to rank

✍ Wang, Yang; Huang, Ya-Lou; Mao-Qiang Xie, ; Jie Liu, ; Min Lu, ; Zhen Liao, 📂 Article 📅 2009 🏛 IEEE ⚖ 691 KB

[ACM Press the 21st ACM international co

[ACM Press the 21st ACM international conference - Maui, Hawaii, USA (2012.10.29-2012.11.02)] Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM '12 - Query-biased learning to rank for real-time twitter search

✍ Zhang, Xin; He, Ben; Luo, Tiejian; Li, Baobin 📂 Article 📅 2012 🏛 ACM Press ⚖ 393 KB

[ACM Press the sixth ACM international c

[ACM Press the sixth ACM international conference - Rome, Italy (2013.02.04-2013.02.08)] Proceedings of the sixth ACM international conference on Web search and data mining - WSDM '13 - Reusing historical interaction data for faster online learning to rank for IR

✍ Hofmann, Katja; Schuth, Anne; Whiteson, Shimon; de Rijke, Maarten 📂 Article 📅 2013 🏛 ACM Press ⚖ 741 KB

[ACM Press the sixth ACM international c

[ACM Press the sixth ACM international conference - Rome, Italy (2013.02.04-2013.02.08)] Proceedings of the sixth ACM international conference on Web search and data mining - WSDM '13 - Reusing historical interaction data for faster online learning to rank for IR

✍ Hofmann, Katja; Schuth, Anne; Whiteson, Shimon; de Rijke, Maarten 📂 Article 📅 2013 🏛 ACM Press ⚖ 741 KB

Online learning to rank for information retrieval (IR) holds promise for allowing the development of "self-learning" search engines that can automatically adjust to their users. With the large amount of e.g., click data that can be collected in web search settings, such techniques could enable highl