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WSDM
2012
ACM
285views Data Mining» more  WSDM 2012»
12 years 5 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...
CIDR
2007
155views Algorithms» more  CIDR 2007»
13 years 11 months ago
Object-level Vertical Search
Current web search engines essentially conduct document-level ranking and retrieval. However, structured information about realworld objects embedded in static webpages and online...
Zaiqing Nie, Ji-Rong Wen, Wei-Ying Ma
AAAI
2007
13 years 12 months ago
Aggregating User-Centered Rankings to Improve Web Search
This paper is to investigate rank aggregation based on multiple user-centered measures in the context of the web search. We introduce a set of techniques to combine ranking lists ...
Lin Li, Zhenglu Yang, Masaru Kitsuregawa
NIPS
2003
13 years 11 months ago
Ranking on Data Manifolds
The Google search engine has enjoyed huge success with its web page ranking algorithm, which exploits global, rather than local, hyperlink structure of the web using random walks....
Dengyong Zhou, Jason Weston, Arthur Gretton, Olivi...
SIGIR
2006
ACM
14 years 3 months ago
AggregateRank: bringing order to web sites
Since the website is one of the most important organizational structures of the Web, how to effectively rank websites has been essential to many Web applications, such as Web sear...
Guang Feng, Tie-Yan Liu, Ying Wang, Ying Bao, Zhim...