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» A general dimension for query learning
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KDD
2008
ACM
186views Data Mining» more  KDD 2008»
14 years 9 months ago
Scalable and near real-time burst detection from eCommerce queries
In large scale online systems like Search, eCommerce, or social network applications, user queries represent an important dimension of activities that can be used to study the imp...
Nish Parikh, Neel Sundaresan
EDBT
2010
ACM
144views Database» more  EDBT 2010»
14 years 8 days ago
Timely YAGO: harvesting, querying, and visualizing temporal knowledge from Wikipedia
Recent progress in information extraction has shown how to automatically build large ontologies from high-quality sources like Wikipedia. But knowledge evolves over time; facts ha...
Yafang Wang, Mingjie Zhu, Lizhen Qu, Marc Spaniol,...
VLDB
2001
ACM
190views Database» more  VLDB 2001»
14 years 1 months ago
LEO - DB2's LEarning Optimizer
Most modern DBMS optimizers rely upon a cost model to choose the best query execution plan (QEP) for any given query. Cost estimates are heavily dependent upon the optimizer’s e...
Michael Stillger, Guy M. Lohman, Volker Markl, Mok...
WWW
2008
ACM
14 years 9 months ago
Using the wisdom of the crowds for keyword generation
In the sponsored search model, search engines are paid by businesses that are interested in displaying ads for their site alongside the search results. Businesses bid for keywords...
Ariel Fuxman, Panayiotis Tsaparas, Kannan Achan, R...
DSMML
2004
Springer
14 years 2 months ago
Can Gaussian Process Regression Be Made Robust Against Model Mismatch?
Learning curves for Gaussian process (GP) regression can be strongly affected by a mismatch between the ‘student’ model and the ‘teacher’ (true data generation process), e...
Peter Sollich