180 search results - page 13 / 36 » Unsupervised Relation Disambiguation Using Spectral Clusteri... |
DATESO
2010
13 years 5 months ago
2010
Abstract. The high dimensionality of the data generated by social networks has been a big challenge for researchers. In order to solve the problems associated with this phenomenon,...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We describe an algorithm for clustering using a similarity graph. The algorithm (a) runs in O(n log3 n + m log n) time on graphs with n vertices and m edges, and (b) with high pro...
TSD
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. Clustering is often considered the most important unsupervised learning problem and several clustering algorithms have been proposed over the years. Many of these algorit...
SDM
2009
SIAM
14 years 5 months ago
2009
SIAM
Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
CVPR
2008
IEEE
14 years 9 months ago
2008
IEEE
Matching articulated shapes represented by voxel-sets reduces to maximal sub-graph isomorphism when each set is described by a weighted graph. Spectral graph theory can be used to...