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» Parallel learning to rank for information retrieval
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ECIR
2011
Springer
12 years 11 months ago
Balancing Exploration and Exploitation in Learning to Rank Online
Abstract. As retrieval systems become more complex, learning to rank approaches are being developed to automatically tune their parameters. Using online learning to rank approaches...
Katja Hofmann, Shimon Whiteson, Maarten de Rijke
SIGIR
2010
ACM
13 years 11 months ago
A ranking approach to target detection for automatic link generation
We focus on the task of target detection in automatic link generation with Wikipedia, i.e., given an N-gram in a snippet of text, find the relevant Wikipedia concepts that explai...
Jiyin He, Maarten de Rijke
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
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
14 years 8 months ago
Query chains: learning to rank from implicit feedback
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Filip Radlinski, Thorsten Joachims
DEXAW
2010
IEEE
196views Database» more  DEXAW 2010»
13 years 7 months ago
Direct Optimization of Evaluation Measures in Learning to Rank Using Particle Swarm
— One of the central issues in Learning to Rank (L2R) for Information Retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures ...
Ósscar Alejo, Juan M. Fernández-Luna...