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» Clustering with XCS on Complex Structure Dataset
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AAAI
2011
12 years 7 months ago
Exploiting Phase Transition in Latent Networks for Clustering
In this paper, we model the pair-wise similarities of a set of documents as a weighted network with a single cutoff parameter. Such a network can be thought of an ensemble of unwe...
Vahed Qazvinian, Dragomir R. Radev
PAKDD
2010
ACM
193views Data Mining» more  PAKDD 2010»
13 years 5 months ago
As Time Goes by: Discovering Eras in Evolving Social Networks
Abstract. Within the large body of research in complex network analysis, an important topic is the temporal evolution of networks. Existing approaches aim at analyzing the evolutio...
Michele Berlingerio, Michele Coscia, Fosca Giannot...
AIRS
2006
Springer
13 years 11 months ago
A Novel Ant-Based Clustering Approach for Document Clustering
Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant Colony Optimization (ACO) is one such algorithm based on s...
Yulan He, Siu Cheung Hui, Yongxiang Sim
ECCV
2008
Springer
14 years 9 months ago
Unsupervised Structure Learning: Hierarchical Recursive Composition, Suspicious Coincidence and Competitive Exclusion
Abstract. We describe a new method for unsupervised structure learning of a hierarchical compositional model (HCM) for deformable objects. The learning is unsupervised in the sense...
Long Zhu, Chenxi Lin, Haoda Huang, Yuanhao Chen, A...
ECAI
2004
Springer
14 years 26 days ago
Learning Complex and Sparse Events in Long Sequences
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
Marco Botta, Ugo Galassi, Attilio Giordana