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» Learning to rank for information retrieval
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INEX
2005
Springer
15 years 12 months ago
INEX 2005 Multimedia Track
In this article the activities of the INEX 2005 Multimedia track are reported. We succesfully realized our objective, to provide an evaluation platform for the evaluation of retrie...
Roelof van Zwol, Gabriella Kazai, Mounia Lalmas
WWW
2009
ACM
16 years 7 months ago
Combining anchor text categorization and graph analysis for paid link detection
In order to artificially boost the rank of commercial pages in search engine results, search engine optimizers pay for links to these pages on other websites. Identifying paid lin...
Kirill Nikolaev, Ekaterina Zudina, Andrey Gorshkov
SIGMOD
2009
ACM
175views Database» more  SIGMOD 2009»
16 years 6 months ago
Ranking distributed probabilistic data
Ranking queries are essential tools to process large amounts of probabilistic data that encode exponentially many possible deterministic instances. In many applications where unce...
Feifei Li, Ke Yi, Jeffrey Jestes
SIGIR
2012
ACM
13 years 8 months ago
Time-sensitive query auto-completion
Query auto-completion (QAC) is a common feature in modern search engines. High quality QAC candidates enhance search experience by saving users time that otherwise would be spent ...
Milad Shokouhi, Kira Radinsky
SIGIR
2008
ACM
15 years 5 months ago
Pagerank based clustering of hypertext document collections
Clustering hypertext document collection is an important task in Information Retrieval. Most clustering methods are based on document content and do not take into account the hype...
Konstantin Avrachenkov, Vladimir Dobrynin, Danil N...