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» Swarming to rank for information retrieval
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ECIR
2009
Springer
16 years 3 months ago
Regression Rank: Learning to Meet the Opportunity of Descriptive Queries
Abstract. We present a new learning to rank framework for estimating context-sensitive term weights without use of feedback. Specifically, knowledge of effective term weights on ...
Matthew Lease, James Allan, W. Bruce Croft
172
Voted
SIGIR
2009
ACM
16 years 20 days ago
Smoothing clickthrough data for web search ranking
Incorporating features extracted from clickthrough data (called clickthrough features) has been demonstrated to significantly improve the performance of ranking models for Web sea...
Jianfeng Gao, Wei Yuan, Xiao Li, Kefeng Deng, Jian...
144
Voted
WWW
2004
ACM
16 years 6 months ago
Distributed ranking over peer-to-peer networks
Query flooding is a problem existing in Peer-to-Peer networks like Gnutella. Firework Query Model solves this problem by Peer Clustering and routes the query message more intellig...
Dexter Chi Wai Siu, Tak Pang Lau
166
Voted
CIKM
2010
Springer
15 years 4 months ago
Semantic tags generation and retrieval for online advertising
One of the main problems in online advertising is to display ads which are relevant and appropriate w.r.t. what the user is looking for. Often search engines fail to reach this go...
Roberto Mirizzi, Azzurra Ragone, Tommaso Di Noia, ...
178
Voted
CIKM
2010
Springer
15 years 4 months ago
Learning to rank relevant and novel documents through user feedback
We consider the problem of learning to rank relevant and novel documents so as to directly maximize a performance metric called Expected Global Utility (EGU), which has several de...
Abhimanyu Lad, Yiming Yang