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ECIR
2009
Springer
14 years 5 months ago
Joint Ranking for Multilingual Web Search
Ranking for multilingual information retrieval (MLIR) is a task to rank documents of different languages solely based on their relevancy to the query regardless of query’s langu...
Wei Gao, Cheng Niu, Ming Zhou, Kam-Fai Wong
WWW
2006
ACM
14 years 9 months ago
Beyond PageRank: machine learning for static ranking
Since the publication of Brin and Page's paper on PageRank, many in the Web community have depended on PageRank for the static (query-independent) ordering of Web pages. We s...
Matthew Richardson, Amit Prakash, Eric Brill
WWW
2009
ACM
14 years 9 months ago
A dynamic bayesian network click model for web search ranking
As with any application of machine learning, web search ranking requires labeled data. The labels usually come in the form of relevance assessments made by editors. Click logs can...
Olivier Chapelle, Ya Zhang
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
14 years 9 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
ECIR
2007
Springer
13 years 10 months ago
A Bayesian Approach for Learning Document Type Relevance
Retrieval accuracy can be improved by considering which document type should be filtered out and which should be ranked higher in the result list. Hence, document type can be used...
Peter C. K. Yeung, Stefan Büttcher, Charles L...