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» A Comparative Evaluation of Term Recognition Algorithms
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GIS
2007
ACM
15 years 10 months ago
Predicting future locations using clusters' centroids
As technology advances we encounter more available data on moving objects, thus increasing our ability to mine spatiotemporal data. We can use this data for learning moving object...
Sigal Elnekave, Mark Last, Oded Maimon
KDD
2004
ACM
151views Data Mining» more  KDD 2004»
16 years 5 months ago
Feature selection in scientific applications
Numerous applications of data mining to scientific data involve the induction of a classification model. In many cases, the collection of data is not performed with this task in m...
Erick Cantú-Paz, Shawn Newsam, Chandrika Ka...
KDD
2010
ACM
222views Data Mining» more  KDD 2010»
15 years 6 months ago
Large linear classification when data cannot fit in memory
Recent advances in linear classification have shown that for applications such as document classification, the training can be extremely efficient. However, most of the existing t...
Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang, Chih-J...
MM
2010
ACM
174views Multimedia» more  MM 2010»
15 years 4 months ago
Image classification using the web graph
Image classification is a well-studied and hard problem in computer vision. We extend a proven solution for classifying web spam to handle images. We exploit the link structure of...
Dhruv Kumar Mahajan, Malcolm Slaney
DIS
2006
Springer
15 years 8 months ago
Clustering Pairwise Distances with Missing Data: Maximum Cuts Versus Normalized Cuts
Abstract. Clustering algorithms based on a matrix of pairwise similarities (kernel matrix) for the data are widely known and used, a particularly popular class being spectral clust...
Jan Poland, Thomas Zeugmann