Large-scale community detection in social networks
There are various community detection algorithms which that have been developed. Among them, Louvain method is the most widely used algorithm because of its simplicity and good performance. The goal of this project is to improve an existing parallel implementation of community detection algorithm ba...
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sg-ntu-dr.10356-520672023-03-03T20:58:11Z Large-scale community detection in social networks Risan. Stephen John Turner School of Computer Engineering A*STAR Institute of High Performance Computing (IHPC) DRNTU::Engineering::Computer science and engineering There are various community detection algorithms which that have been developed. Among them, Louvain method is the most widely used algorithm because of its simplicity and good performance. The goal of this project is to improve an existing parallel implementation of community detection algorithm based on Louvain method that works on multiple GPU. This project empirically studies existing partitioning methods, memory and running time optimization. As the result of the studies, a new partitioning method was proposed to decrease the running time of overall algorithm. The functionality was also expanded by allowing weighted network as input. In addition, the running time of modularity computation was also improved. Bachelor of Engineering (Computer Science) 2013-04-22T03:57:24Z 2013-04-22T03:57:24Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/52067 en Nanyang Technological University 57 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering Risan. Large-scale community detection in social networks |
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There are various community detection algorithms which that have been developed. Among them, Louvain method is the most widely used algorithm because of its simplicity and good performance. The goal of this project is to improve an existing parallel implementation of community detection algorithm based on Louvain method that works on multiple GPU. This project empirically studies existing partitioning methods, memory and running time optimization. As the result of the studies, a new partitioning method was proposed to decrease the running time of overall algorithm. The functionality was also expanded by allowing weighted network as input. In addition, the running time of modularity computation was also improved. |
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Stephen John Turner |
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Stephen John Turner Risan. |
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Final Year Project |
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Large-scale community detection in social networks |
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Large-scale community detection in social networks |
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Large-scale community detection in social networks |
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Large-scale community detection in social networks |
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Large-scale community detection in social networks |
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large-scale community detection in social networks |
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2013 |
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http://hdl.handle.net/10356/52067 |
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