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IIS
2003
15 years 8 months ago
Ontology-based Text Document Clustering
Text clustering typically involves clustering in a high dimensional space, which appears difficult with regard to virtually all practical settings. In addition, given a particular...
Steffen Staab, Andreas Hotho
NIPS
2003
15 years 8 months ago
Clustering with the Connectivity Kernel
Clustering aims at extracting hidden structure in dataset. While the problem of finding compact clusters has been widely studied in the literature, extracting arbitrarily formed ...
Bernd Fischer, Volker Roth, Joachim M. Buhmann
DMIN
2009
222views Data Mining» more  DMIN 2009»
15 years 4 months ago
P-Sensitive K-Anonymity for Social Networks
-- The proliferation of social networks, where individuals share private information, has caused, in the last few years, a growth in the volume of sensitive data being stored in th...
Roy Ford, Traian Marius Truta, Alina Campan
AAAI
2011
14 years 6 months ago
Improving Semi-Supervised Support Vector Machines Through Unlabeled Instances Selection
Semi-supervised support vector machines (S3VMs) are a kind of popular approaches which try to improve learning performance by exploiting unlabeled data. Though S3VMs have been fou...
Yu-Feng Li, Zhi-Hua Zhou
KDD
2002
ACM
152views Data Mining» more  KDD 2002»
16 years 7 months ago
Multimedia Data Mining Framework For Raw Video Sequences
In this paper, we propose a general framework for real time video data mining to be applied to the raw videos (traffic videos, surveillance videos, etc.). We investigate whether t...
Jung-Hwan Oh, Babitha Bandi