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
โฆ LIBER โฆ
[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
โ Scribed by Hofmann, Katja; Schuth, Anne; Whiteson, Shimon; de Rijke, Maarten
- Book ID
- 125459414
- Publisher
- ACM Press
- Year
- 2013
- Weight
- 741 KB
- Category
- Article
- ISBN
- 145031869X
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