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ICML
2010
IEEE
15 years 7 months ago
Metric Learning to Rank
We study metric learning as a problem of information retrieval. We present a general metric learning algorithm, based on the structural SVM framework, to learn a metric such that ...
Brian McFee, Gert R. G. Lanckriet
CIKM
2010
Springer
15 years 5 months ago
FacetCube: a framework of incorporating prior knowledge into non-negative tensor factorization
Non-negative tensor factorization (NTF) is a relatively new technique that has been successfully used to extract significant characteristics from polyadic data, such as data in s...
Yun Chi, Shenghuo Zhu
KDD
2005
ACM
178views Data Mining» more  KDD 2005»
16 years 9 days ago
Failure detection and localization in component based systems by online tracking
The increasing complexity of today’s systems makes fast and accurate failure detection essential for their use in mission-critical applications. Various monitoring methods provi...
Haifeng Chen, Guofei Jiang, Cristian Ungureanu, Ke...
SDM
2010
SIAM
146views Data Mining» more  SDM 2010»
15 years 8 months ago
Towards Finding Valuable Topics
Enterprises depend on their information workers finding valuable information to be productive. However, existing enterprise search and recommendation systems can exploit few studi...
Zhen Wen, Ching-Yung Lin
SIGIR
2012
ACM
13 years 9 months ago
To index or not to index: time-space trade-offs in search engines with positional ranking functions
Positional ranking functions, widely used in web search engines, improve result quality by exploiting the positions of the query terms within documents. However, it is well known ...
Diego Arroyuelo, Senén González, Mau...