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CVPR
2003
IEEE
14 years 10 months ago
Object Class Recognition by Unsupervised Scale-Invariant Learning
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
Robert Fergus, Pietro Perona, Andrew Zisserman
WWW
2008
ACM
14 years 9 months ago
Unsupervised query segmentation using generative language models and wikipedia
In this paper, we propose a novel unsupervised approach to query segmentation, an important task in Web search. We use a generative query model to recover a query's underlyin...
Bin Tan, Fuchun Peng
WACV
2005
IEEE
14 years 2 months ago
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Thomas S. Stepleton, Tai Sing Lee
ICML
2005
IEEE
14 years 9 months ago
Learn to weight terms in information retrieval using category information
How to assign appropriate weights to terms is one of the critical issues in information retrieval. Many term weighting schemes are unsupervised. They are either based on the empir...
Rong Jin, Joyce Y. Chai, Luo Si
WWW
2011
ACM
13 years 3 months ago
Unsupervised query segmentation using only query logs
We introduce an unsupervised query segmentation scheme that uses query logs as the only resource and can effectively capture the structural units in queries. We believe that Web s...
Nikita Mishra, Rishiraj Saha Roy, Niloy Ganguly, S...