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ICDM
2010
IEEE
230views Data Mining» more  ICDM 2010»
13 years 2 months ago
Clustering Large Attributed Graphs: An Efficient Incremental Approach
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
Yang Zhou, Hong Cheng, Jeffrey Xu Yu
AAAI
2008
13 years 6 months ago
Visualization of Large-Scale Weighted Clustered Graph: A Genetic Approach
In this paper, a bottom-up hierarchical genetic algorithm is proposed to visualize clustered data into a planar graph. To achieve global optimization by accelerating local optimiz...
Jiayu Zhou, Youfang Lin, Xi Wang
SDM
2009
SIAM
160views Data Mining» more  SDM 2009»
14 years 1 months ago
Discovering Substantial Distinctions among Incremental Bi-Clusters.
A fundamental task of data analysis is comprehending what distinguishes clusters found within the data. We present the problem of mining distinguishing sets which seeks to find s...
Faris Alqadah, Raj Bhatnagar
KDD
2007
ACM
152views Data Mining» more  KDD 2007»
14 years 4 months ago
Efficient incremental constrained clustering
Clustering with constraints is an emerging area of data mining research. However, most work assumes that the constraints are given as one large batch. In this paper we explore the...
Ian Davidson, S. S. Ravi, Martin Ester
SIAMSC
2008
182views more  SIAMSC 2008»
13 years 4 months ago
A Distributed SDP Approach for Large-Scale Noisy Anchor-Free Graph Realization with Applications to Molecular Conformation
We propose a distributed algorithm for solving Euclidean metric realization problems arising from large 3D graphs, using only noisy distance information, and without any prior kno...
Pratik Biswas, Kim-Chuan Toh, Yinyu Ye