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217
Voted
WSDM
2012
ACM
285views Data Mining» more  WSDM 2012»
14 years 2 months ago
Probabilistic models for personalizing web search
We present a new approach for personalizing Web search results to a specific user. Ranking functions for Web search engines are typically trained by machine learning algorithms u...
David Sontag, Kevyn Collins-Thompson, Paul N. Benn...
193
Voted
CIKM
2008
Springer
15 years 8 months ago
Are click-through data adequate for learning web search rankings?
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
Zhicheng Dou, Ruihua Song, Xiaojie Yuan, Ji-Rong W...
WWW
2009
ACM
16 years 7 months ago
Estimating the impressionrank of web pages
The ImpressionRank of a web page (or, more generally, of a web site) is the number of times users viewed the page while browsing search results. ImpressionRank captures the visibi...
Ziv Bar-Yossef, Maxim Gurevich
151
Voted
SIGIR
2010
ACM
15 years 10 months ago
Studying trailfinding algorithms for enhanced web search
Search engines return ranked lists of Web pages in response to queries. These pages are starting points for post-query navigation, but may be insufficient for search tasks involvi...
Adish Singla, Ryen White, Jeff Huang
203
Voted
SIGIR
2008
ACM
15 years 6 months ago
Automatically identifying localizable queries
Personalization of web search results as a technique for improving user satisfaction has received notable attention in the research community over the past decade. Much of this wo...
Michael J. Welch, Junghoo Cho