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» Learning to rank for information retrieval
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SIGIR
2011
ACM
14 years 9 months ago
A boosting approach to improving pseudo-relevance feedback
Pseudo-relevance feedback has proven effective for improving the average retrieval performance. Unfortunately, many experiments have shown that although pseudo-relevance feedback...
Yuanhua Lv, ChengXiang Zhai, Wan Chen
CIKM
2004
Springer
15 years 11 months ago
Local methods for estimating pagerank values
The Google search engine uses a method called PageRank, together with term-based and other ranking techniques, to order search results returned to the user. PageRank uses link ana...
Yen-Yu Chen, Qingqing Gan, Torsten Suel
WEBI
2010
Springer
15 years 4 months ago
How to Improve Your Google Ranking: Myths and Reality
Abstract--Search engines have greatly influenced the way people access information on the Internet as such engines provide the preferred entry point to billions of pages on the Web...
Ao-Jan Su, Y. Charlie Hu, Aleksandar Kuzmanovic, C...
AIRWEB
2007
Springer
16 years 15 days ago
Computing Trusted Authority Scores in Peer-to-Peer Web Search Networks
Peer-to-peer (P2P) networks have received great attention for sharing and searching information in large user communities. The open and anonymous nature of P2P networks is one of ...
Josiane Xavier Parreira, Debora Donato, Carlos Cas...
WWW
2007
ACM
16 years 7 months ago
Predicting clicks: estimating the click-through rate for new ads
Search engine advertising has become a significant element of the Web browsing experience. Choosing the right ads for the query and the order in which they are displayed greatly a...
Matthew Richardson, Ewa Dominowska, Robert Ragno