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» Significance-Driven Graph Clustering
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94
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WABI
2007
Springer
15 years 6 months ago
A Graph Clustering Approach to Weak Motif Recognition
The aim of the motif recognition problem is to detect a set of mutually similar subsequences within a collection of biological sequences. The weak motif recognition problem on DNA ...
Christina Boucher, Daniel G. Brown, Paul Church
105
Voted
ISAAC
2004
Springer
121views Algorithms» more  ISAAC 2004»
15 years 6 months ago
Approximate Distance Oracles for Graphs with Dense Clusters
Let G be a graph containing N disjoint t-spanners that are inter-connected with M edges. We present an algorithm that constructs a data structure of size O(M2 + n log n) that answ...
Mattias Andersson, Joachim Gudmundsson, Christos L...
ACL
2007
15 years 2 months ago
Computing Lexical Chains with Graph Clustering
This paper describes a new method for computing lexical chains. These are sequences of semantically related words that reflect a text’s cohesive structure. In contrast to previo...
Olena Medelyan
109
Voted
APVIS
2010
15 years 2 months ago
GMap: Visualizing graphs and clusters as maps
Information visualization is essential in making sense out of large data sets. Often, high-dimensional data are visualized as a collection of points in 2-dimensional space through...
Emden R. Gansner, Yifan Hu, Stephen G. Kobourov
95
Voted
APVIS
2008
15 years 2 months ago
Visual Statistics for Collections of Clustered Graphs
We propose a method to visually summarize collections of networks on which a clustering of the vertices is given. Our method allows for efficient comparison of individual networks...
Ulrik Brandes, Jürgen Lerner, Miranda J. Lubb...