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Rescooped by Jean-Michel Livowsky from Influence et contagion
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A taxonomy of #clustering procedures | #datascience


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Rescooped by Jean-Michel Livowsky from e-Xploration
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A smart local moving #algorithm for large-scale modularity-based community detection | #SNA #clustering

A smart local moving #algorithm for large-scale modularity-based community detection | #SNA #clustering | Intelligence | Scoop.it

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luiy's curator insight, November 15, 2013 10:41 AM

Our smart local moving (SLM) algorithm is an algorithm for community detection (or clustering) in large networks. The SLM algorithm maximizes a so-called modularity function. The algorithm has been successfully applied to networks with tens of millions of nodes and hundreds of millions of edges. The details of the algorithm are documented in a paper (preprint available here).

 

The SLM algorithm has been implemented in the Modularity Optimizer, a simple command-line computer program written in Java. The Modularity Optimizer can be freely downloaded. The program can be run on any system that supports Java version 1.6 or higher. In addition to the SLM algorithm, the Modularity Optimizer also provides an implementation of the well-known Louvain algorithm for large-scale community detection developed by Vincent Blondel and colleagues. An extension of the Louvain algorithm with a multilevel refinement procedure, as proposed by Randolf Rotta and Andreas Noack, is implemented as well. All algorithms implemented in the Modularity Optimizer support the use of a resolution parameter to determine the granularity level at which communities are detected.

Jean-Michel Livowsky's curator insight, November 16, 2013 8:38 AM

SLM algoritm. Very nice move in this complex approach of collective intelligence.

Rescooped by Jean-Michel Livowsky from e-Xploration
Scoop.it!

A smart local moving #algorithm for large-scale modularity-based community detection | #SNA #clustering

A smart local moving #algorithm for large-scale modularity-based community detection | #SNA #clustering | Intelligence | Scoop.it

Via luiy
more...
luiy's curator insight, November 15, 2013 10:41 AM

Our smart local moving (SLM) algorithm is an algorithm for community detection (or clustering) in large networks. The SLM algorithm maximizes a so-called modularity function. The algorithm has been successfully applied to networks with tens of millions of nodes and hundreds of millions of edges. The details of the algorithm are documented in a paper (preprint available here).

 

The SLM algorithm has been implemented in the Modularity Optimizer, a simple command-line computer program written in Java. The Modularity Optimizer can be freely downloaded. The program can be run on any system that supports Java version 1.6 or higher. In addition to the SLM algorithm, the Modularity Optimizer also provides an implementation of the well-known Louvain algorithm for large-scale community detection developed by Vincent Blondel and colleagues. An extension of the Louvain algorithm with a multilevel refinement procedure, as proposed by Randolf Rotta and Andreas Noack, is implemented as well. All algorithms implemented in the Modularity Optimizer support the use of a resolution parameter to determine the granularity level at which communities are detected.

Jean-Michel Livowsky's curator insight, November 16, 2013 8:38 AM

SLM algoritm. Very nice move in this complex approach of collective intelligence.

Rescooped by Jean-Michel Livowsky from e-Xploration
Scoop.it!

A smart local moving #algorithm for large-scale modularity-based community detection | #SNA #clustering

A smart local moving #algorithm for large-scale modularity-based community detection | #SNA #clustering | Intelligence | Scoop.it

Via luiy
Jean-Michel Livowsky's insight:

SLM algoritm. Very nice move in this complex approach of collective intelligence.

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luiy's curator insight, November 15, 2013 10:41 AM

Our smart local moving (SLM) algorithm is an algorithm for community detection (or clustering) in large networks. The SLM algorithm maximizes a so-called modularity function. The algorithm has been successfully applied to networks with tens of millions of nodes and hundreds of millions of edges. The details of the algorithm are documented in a paper (preprint available here).

 

The SLM algorithm has been implemented in the Modularity Optimizer, a simple command-line computer program written in Java. The Modularity Optimizer can be freely downloaded. The program can be run on any system that supports Java version 1.6 or higher. In addition to the SLM algorithm, the Modularity Optimizer also provides an implementation of the well-known Louvain algorithm for large-scale community detection developed by Vincent Blondel and colleagues. An extension of the Louvain algorithm with a multilevel refinement procedure, as proposed by Randolf Rotta and Andreas Noack, is implemented as well. All algorithms implemented in the Modularity Optimizer support the use of a resolution parameter to determine the granularity level at which communities are detected.