18 search results - page 3 / 4 » Document clustering via adaptive subspace iteration |
CVPR
2007
IEEE
14 years 7 months ago
2007
IEEE
A good distance metric is crucial for unsupervised learning from high-dimensional data. To learn a metric without any constraint or class label information, most unsupervised metr...
CIKM
2007
Springer
13 years 11 months ago
2007
Springer
We consider the problem of document indexing and representation. Recently, Locality Preserving Indexing (LPI) was proposed for learning a compact document subspace. Different from...
KDD
2007
ACM
14 years 5 months ago
2007
ACM
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
JCDL
2003
ACM
13 years 10 months ago
2003
ACM
Automatic metadata generation provides scalability and usability for digital libraries and their collections. Machine learning methods offer robust and adaptable automatic metadat...
SIGIR
2010
ACM
13 years 5 months ago
2010
ACM
Cluster label quality is crucial for browsing topic hierarchies obtained via document clustering. Intuitively, the hierarchical structure should influence the labeling accuracy. H...