Sciweavers
Explore
Publications
Books
Software
Tutorials
Presentations
Lectures Notes
Datasets
Labs
Conferences
Community
Upcoming
Conferences
Top Ranked Papers
Most Viewed Conferences
Conferences by Acronym
Conferences by Subject
Conferences by Year
Tools
Sci2ools
International Keyboard
Graphical Social Symbols
CSS3 Style Generator
OCR
Web Page to Image
Web Page to PDF
Merge PDF
Split PDF
Latex Equation Editor
Extract Images from PDF
Convert JPEG to PS
Convert Latex to Word
Convert Word to PDF
Image Converter
PDF Converter
Community
Sciweavers
About
Terms of Use
Privacy Policy
Cookies
Free Online Productivity Tools
i2Speak
i2Symbol
i2OCR
iTex2Img
iWeb2Print
iWeb2Shot
i2Type
iPdf2Split
iPdf2Merge
i2Bopomofo
i2Arabic
i2Style
i2Image
i2PDF
iLatex2Rtf
Sci2ools
26
click to vote
WSDM
2010
ACM
favorite
Email
discuss
report
187
views
Data Mining
»
more
WSDM 2010
»
Precomputing search features for fast and accurate query classification
14 years 5 months ago
Download
research.microsoft.com
Venkatesh Ganti, Arnd Christian König, Xiao L
Real-time Traffic
Data Mining
|
WSDM 2010
|
claim paper
Related Content
»
Application of Kernel Functions for Accurate Similarity Search in Large Chemical Databases
»
Improving Automatic Query Classification via SemiSupervised Learning
»
Coupling feature selection and machine learning methods for navigational query identificat...
»
Contentbased audio classification and retrieval using a fuzzy logic system towards multime...
»
FISH a practical system for fast interactive image search in huge databases
»
Ghash towards fast kernelbased similarity search in large graph databases
»
Automatic web query classification using labeled and unlabeled training data
»
DDPIn Distance and density based protein indexing
»
Kernelized LocalitySensitive Hashing for Scalable Image Search
more »
Post Info
More Details (n/a)
Added
18 May 2010
Updated
18 May 2010
Type
Conference
Year
2010
Where
WSDM
Authors
Venkatesh Ganti, Arnd Christian König, Xiao Li
Comments
(0)
Researcher Info
Data Mining Study Group
Computer Vision