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» Adapting ranking SVM to document retrieval
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SIGIR
2002
ACM
13 years 7 months ago
A new family of online algorithms for category ranking
We describe a new family of topic-ranking algorithms for multi-labeled documents. The motivation for the algorithms stems from recent advances in online learning algorithms. The a...
Koby Crammer, Yoram Singer
WWW
2002
ACM
14 years 8 months ago
Using web structure for classifying and describing web pages
The structure of the web is increasingly being used to improve organization, search, and analysis of information on the web. For example, Google uses the text in citing documents ...
Eric J. Glover, Kostas Tsioutsiouliklis, Steve Law...
CIKM
2010
Springer
13 years 6 months ago
Clickthrough-based translation models for web search: from word models to phrase models
Web search is challenging partly due to the fact that search queries and Web documents use different language styles and vocabularies. This paper provides a quantitative analysis ...
Jianfeng Gao, Xiaodong He, Jian-Yun Nie
ICTIR
2009
Springer
14 years 2 months ago
Modeling Expected Utility of Multi-session Information Distillation
Abstract. An open challenge in information distillation is the evaluation and optimization of the utility of ranked lists with respect to flexible user interactions over multiple ...
Yiming Yang, Abhimanyu Lad
CIKM
2008
Springer
13 years 9 months ago
Are click-through data adequate for learning web search rankings?
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
Zhicheng Dou, Ruihua Song, Xiaojie Yuan, Ji-Rong W...