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» Clustering Improves the Exploration of Graph Mining Results
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KDD
2007
ACM
178views Data Mining» more  KDD 2007»
16 years 4 days ago
Density-based clustering for real-time stream data
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
Yixin Chen, Li Tu
SDM
2009
SIAM
192views Data Mining» more  SDM 2009»
15 years 9 months ago
Mining Cohesive Patterns from Graphs with Feature Vectors.
The increasing availability of network data is creating a great potential for knowledge discovery from graph data. In many applications, feature vectors are given in addition to g...
Arash Rafiey, Flavia Moser, Martin Ester, Recep Co...
KDD
2006
ACM
198views Data Mining» more  KDD 2006»
16 years 4 days ago
Event detection from evolution of click-through data
Previous efforts on event detection from the web have focused primarily on web content and structure data ignoring the rich collection of web log data. In this paper, we propose t...
Qiankun Zhao, Tie-Yan Liu, Sourav S. Bhowmick, Wei...
AAAI
2007
15 years 2 months ago
Clustering with Local and Global Regularization
Clustering is an old research topic in data mining and machine learning communities. Most of the traditional clustering methods can be categorized local or global ones. In this pa...
Fei Wang, Changshui Zhang, Tao Li
MMDB
2004
ACM
148views Multimedia» more  MMDB 2004»
15 years 5 months ago
A unified framework for image database clustering and content-based retrieval
With the proliferation of image data, the need to search and retrieve images efficiently and accurately from a large image database or a collection of image databases has drastica...
Mei-Ling Shyu, Shu-Ching Chen, Min Chen, Chengcui ...