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» Learning effective ranking functions for newsgroup search
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KDD
2008
ACM
147views Data Mining» more  KDD 2008»
14 years 8 months ago
Structured learning for non-smooth ranking losses
Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major te...
Soumen Chakrabarti, Rajiv Khanna, Uma Sawant, Chir...
EMNLP
2009
13 years 5 months ago
Empirical Exploitation of Click Data for Task Specific Ranking
There have been increasing needs for task specific rankings in web search such as rankings for specific query segments like long queries, time-sensitive queries, navigational quer...
Anlei Dong, Yi Chang, Shihao Ji, Ciya Liao, Xin Li...
KDD
2009
ACM
245views Data Mining» more  KDD 2009»
14 years 8 months ago
Mining rich session context to improve web search
User browsing information, particularly their non-search related activity, reveals important contextual information on the preferences and the intent of web users. In this paper, ...
Guangyu Zhu, Gilad Mishne
CIKM
2006
Springer
13 years 11 months ago
Incorporating query difference for learning retrieval functions in world wide web search
We discuss information retrieval methods that aim at serving a diverse stream of user queries such as those submitted to commercial search engines. We propose methods that emphasi...
Hongyuan Zha, Zhaohui Zheng, Haoying Fu, Gordon Su...
CIKM
2010
Springer
13 years 6 months ago
Learning to rank relevant and novel documents through user feedback
We consider the problem of learning to rank relevant and novel documents so as to directly maximize a performance metric called Expected Global Utility (EGU), which has several de...
Abhimanyu Lad, Yiming Yang