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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»
15 years 10 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
103
Voted
ICDM
2003
IEEE
210views Data Mining» more  ICDM 2003»
15 years 2 months 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
15 years 1 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....
79
Voted
ICML
2010
IEEE
14 years 10 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»
15 years 10 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