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» A Very Fast Method for Clustering Big Text Datasets
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KDD
2004
ACM
103views Data Mining» more  KDD 2004»
14 years 7 months ago
An objective evaluation criterion for clustering
We propose and test an objective criterion for evaluation of clustering performance: How well does a clustering algorithm run on unlabeled data aid a classification algorithm? The...
Arindam Banerjee, John Langford
ICDM
2003
IEEE
210views Data Mining» more  ICDM 2003»
14 years 8 days ago
CBC: Clustering Based Text Classification Requiring Minimal Labeled Data
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
Hua-Jun Zeng, Xuanhui Wang, Zheng Chen, Hongjun Lu...
DAS
2010
Springer
13 years 10 months ago
Handwritten Arabic text line segmentation using affinity propagation
In this paper, we present a novel graph-based method for extracting handwritten text lines in monochromatic Arabic document images. Our approach consists of two steps Coarse text ...
Jayant Kumar, Wael Abd-Almageed, Le Kang, David S....
ICML
2010
IEEE
13 years 8 months ago
Power Iteration Clustering
We present a simple and scalable graph clustering method called power iteration clustering (PIC). PIC finds a very low-dimensional embedding of a dataset using truncated power ite...
Frank Lin, William W. Cohen
KDD
2002
ACM
1075views Data Mining» more  KDD 2002»
14 years 7 months ago
CLOPE: a fast and effective clustering algorithm for transactional data
This paper studies the problem of categorical data clustering, especially for transactional data characterized by high dimensionality and large volume. Starting from a heuristic m...
Yiling Yang, Xudong Guan, Jinyuan You