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» Clustering Improves the Exploration of Graph Mining Results
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EUROPAR
2001
Springer
13 years 9 months ago
Experiments in Parallel Clustering with DBSCAN
We present a new result concerning the parallelisation of DBSCAN, a Data Mining algorithm for density-based spatial clustering. The overall structure of DBSCAN has been mapped to a...
Domenica Arlia, Massimo Coppola
CGF
2010
118views more  CGF 2010»
13 years 5 months ago
The Readability of Path-Preserving Clusterings of Graphs
Graph visualization systems often exploit opaque metanodes to reduce visual clutter and improve the readability of large graphs. This filtering can be done in a path-preserving wa...
Daniel Archambault, Helen C. Purchase, Bruno Pinau...
KDD
2004
ACM
145views Data Mining» more  KDD 2004»
13 years 10 months ago
A graph-theoretic approach to extract storylines from search results
We present a graph-theoretic approach to discover storylines from search results. Storylines are windows that offer glimpses into interesting themes latent among the top search re...
Ravi Kumar, Uma Mahadevan, D. Sivakumar
ICDM
2005
IEEE
190views Data Mining» more  ICDM 2005»
13 years 11 months ago
Adaptive Clustering: Obtaining Better Clusters Using Feedback and Past Experience
Adaptive clustering uses external feedback to improve cluster quality; past experience serves to speed up execution time. An adaptive clustering environment is proposed that uses ...
Abraham Bagherjeiran, Christoph F. Eick, Chun-Shen...
KDD
2007
ACM
184views Data Mining» more  KDD 2007»
14 years 5 months ago
Dynamic hybrid clustering of bioinformatics by incorporating text mining and citation analysis
To unravel the concept structure and dynamics of the bioinformatics field, we analyze a set of 7401 publications from the Web of Science and MEDLINE databases, publication years 1...
Bart De Moor, Frizo A. L. Janssens, Wolfgang Gl&au...