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» A machine learning approach for improved BM25 retrieval
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ICML
2009
IEEE
14 years 10 months ago
BoltzRank: learning to maximize expected ranking gain
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
Maksims Volkovs, Richard S. Zemel
ESWS
2007
Springer
14 years 3 months ago
Semantic Process Retrieval with iSPARQL
Abstract. The vision of semantic business processes is to enable the integration and inter-operability of business processes across organizational boundaries. Since different orga...
Christoph Kiefer, Abraham Bernstein, Hong Joo Lee,...
IPM
2008
100views more  IPM 2008»
13 years 9 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...
SIGIR
2010
ACM
14 years 1 months ago
Clicked phrase document expansion for sponsored search ad retrieval
We present a document expansion approach that uses Conditional Random Field (CRF) segmentation to automatically extract salient phrases from ad titles. We then supplement the ad d...
Dustin Hillard, Chris Leggetter
ICML
2005
IEEE
14 years 10 months ago
Recycling data for multi-agent learning
Learning agents can improve performance cooperating with other agents, particularly learning agents forming a committee outperform individual agents. This "ensemble effect&qu...
Santiago Ontañón, Enric Plaza