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» Comparing relevance feedback algorithms for web search
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PAAPP
2007
109views more  PAAPP 2007»
13 years 7 months ago
Relation rule mining
\Web users are nowadays confronted with the huge variety of available information sources whose content is not targeted at any specific group or layer. Recommendation systems aim...
Mehdi Adda, Rokia Missaoui, Petko Valtchev
RECSYS
2010
ACM
13 years 8 months ago
Global budgets for local recommendations
We present the design, implementation and evaluation of a new geotagging service, Gloe, that makes it easy to find, rate and recommend arbitrary on-line content in a mobile settin...
Thomas Sandholm, Hang Ung, Christina Aperjis, Bern...
WWW
2008
ACM
14 years 8 months ago
LocalSavvy: aggregating local points of view about news issues
The web has become an important medium for news delivery and consumption. Fresh content about a variety of topics, events, and places is constantly being created and published on ...
Jiahui Liu, Larry Birnbaum
WWW
2008
ACM
14 years 8 months ago
Recrawl scheduling based on information longevity
It is crucial for a web crawler to distinguish between ephemeral and persistent content. Ephemeral content (e.g., quote of the day) is usually not worth crawling, because by the t...
Christopher Olston, Sandeep Pandey
CSCW
2006
ACM
14 years 2 months ago
Don't look stupid: avoiding pitfalls when recommending research papers
If recommenders are to help people be more productive, they need to support a wide variety of real-world information seeking tasks, such as those found when seeking research paper...
Sean M. McNee, Nishikant Kapoor, Joseph A. Konstan