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» Learning via Finitely Many Queries
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SIGIR
2009
ACM
13 years 12 months 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...
SIGIR
2010
ACM
13 years 9 months ago
Self-taught hashing for fast similarity search
The ability of fast similarity search at large scale is of great importance to many Information Retrieval (IR) applications. A promising way to accelerate similarity search is sem...
Dell Zhang, Jun Wang, Deng Cai, Jinsong Lu
IJCNN
2000
IEEE
13 years 9 months ago
Piecewise Linear Homeomorphisms: The Scalar Case
The class of piecewise linear homeomorphisms (PLH) provides a convenient functional representation for many applications wherein an approximation to data is required that is inver...
Richard E. Groff, Daniel E. Koditschek, Pramod P. ...
AIRWEB
2005
Springer
13 years 11 months ago
An Analysis of Factors Used in Search Engine Ranking
This paper investigates the influence of different page features on the ranking of search engine results. We use Google (via its API) as our testbed and analyze the result rankin...
Albert Bifet, Carlos Castillo, Paul-Alexandru Chir...