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GECCO
2008
Springer
171views Optimization» more  GECCO 2008»
13 years 10 months ago
Particle swarm clustering ensemble
Extracting natural groups of the unlabeled data is known as clustering. To improve the stability and robustness of the clustering outputs, clustering ensembles have emerged recent...
Abbas Ahmadi, Fakhri Karray, Mohamed Kamel
WWW
2010
ACM
14 years 3 months ago
A scalable machine-learning approach for semi-structured named entity recognition
Named entity recognition studies the problem of locating and classifying parts of free text into a set of predefined categories. Although extensive research has focused on the de...
Utku Irmak, Reiner Kraft
BMCBI
2007
178views more  BMCBI 2007»
13 years 9 months ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat
CIKM
2010
Springer
13 years 7 months ago
Combining link and content for collective active learning
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...
Lixin Shi, Yuhang Zhao, Jie Tang
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
14 years 9 months ago
Spectral domain-transfer learning
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Qiang Yang, ...