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PKDD
2010
Springer
235views Data Mining» more  PKDD 2010»
15 years 2 months ago
Online Structural Graph Clustering Using Frequent Subgraph Mining
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...
Madeleine Seeland, Tobias Girschick, Fabian Buchwa...
PKDD
1999
Springer
130views Data Mining» more  PKDD 1999»
15 years 8 months ago
OPTICS-OF: Identifying Local Outliers
: For many KDD applications finding the outliers, i.e. the rare events, is more interesting and useful than finding the common cases, e.g. detecting criminal activities in E-commer...
Markus M. Breunig, Hans-Peter Kriegel, Raymond T. ...
CSDA
2006
82views more  CSDA 2006»
15 years 4 months ago
Nearest neighbours in least-squares data imputation algorithms with different missing patterns
Methods for imputation of missing data in the so-called least-squares approximation approach, a non-parametric computationally efficient multidimensional technique, are experiment...
Ito Wasito, Boris Mirkin
CVPR
2009
IEEE
15 years 11 months ago
Trajectory parsing by cluster sampling in spatio-temporal graph
The objective of this paper is to parse object trajectories in surveillance video against occlusion, interruption, and background clutter. We present a spatio-temporal graph (ST-G...
Xiaobai Liu, Liang Lin, Song Chun Zhu, Hai Jin
WWW
2010
ACM
15 years 11 months ago
The paths more taken: matching DOM trees to search logs for accurate webpage clustering
An unsupervised clustering of the webpages on a website is a primary requirement for most wrapper induction and automated data extraction methods. Since page content can vary dras...
Deepayan Chakrabarti, Rupesh R. Mehta