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WSDM
2009
ACM
104views Data Mining» more  WSDM 2009»
14 years 1 months ago
Top-k aggregation using intersections of ranked inputs
There has been considerable past work on efficiently computing top k objects by aggregating information from multiple ranked lists of these objects. An important instance of this...
Ravi Kumar, Kunal Punera, Torsten Suel, Sergei Vas...
WSDM
2009
ACM
158views Data Mining» more  WSDM 2009»
14 years 1 months ago
A new visual search interface for web browsing
We introduce a new visual search interface for search engines. The interface is a user-friendly and informative graphical front-end for organizing and presenting search results in...
Songhua Xu, Tao Jin, Francis Chi-Moon Lau
WSDM
2009
ACM
115views Data Mining» more  WSDM 2009»
14 years 1 months ago
Discovering and using groups to improve personalized search
Personalized Web search takes advantage of information about an individual to identify the most relevant results for that person. A challenge for personalization lies in collectin...
Jaime Teevan, Meredith Ringel Morris, Steve Bush
WSDM
2009
ACM
176views Data Mining» more  WSDM 2009»
14 years 1 months ago
The web changes everything: understanding the dynamics of web content
The Web is a dynamic, ever changing collection of information. This paper explores changes in Web content by analyzing a crawl of 55,000 Web pages, selected to represent different...
Eytan Adar, Jaime Teevan, Susan T. Dumais, Jonatha...
WSDM
2009
ACM
191views Data Mining» more  WSDM 2009»
14 years 1 months ago
Generating labels from clicks
The ranking function used by search engines to order results is learned from labeled training data. Each training point is a (query, URL) pair that is labeled by a human judge who...
Rakesh Agrawal, Alan Halverson, Krishnaram Kenthap...