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» Aggregating User-Centered Rankings to Improve Web Search
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KDD
2007
ACM
192views Data Mining» more  KDD 2007»
14 years 7 months ago
Active exploration for learning rankings from clickthrough data
We address the task of learning rankings of documents from search engine logs of user behavior. Previous work on this problem has relied on passively collected clickthrough data. ...
Filip Radlinski, Thorsten Joachims
SIGIR
2006
ACM
14 years 22 days ago
Learning user interaction models for predicting web search result preferences
Evaluating user preferences of web search results is crucial for search engine development, deployment, and maintenance. We present a real-world study of modeling the behavior of ...
Eugene Agichtein, Eric Brill, Susan T. Dumais, Rob...
SIGIR
2010
ACM
13 years 10 months ago
Freshness matters: in flowers, food, and web authority
The collective contributions of billions of users across the globe each day result in an ever-changing web. In verticals like news and real-time search, recency is an obvious sign...
Na Dai, Brian D. Davison
ICITA
2005
IEEE
14 years 11 days ago
Partition-Based Parallel PageRank Algorithm
A re-ranking technique,called “PageRank brings a successful story behind the search engine. Many studies focus on finding an way to compute the PageRank scores of a large web gr...
Arnon Rungsawang, Bundit Manaskasemsak
CIKM
2004
Springer
14 years 5 days ago
Node ranking in labeled directed graphs
Our work is motivated by the problem of ranking hyperlinked documents for a given query. Given an arbitrary directed graph with edge and node labels, we present a new flow-based ...
Krishna Prasad Chitrapura, Srinivas R. Kashyap