کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
478504 | 1446103 | 2011 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Spectral methods for graph clustering – A survey
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
Graph clustering is an area in cluster analysis that looks for groups of related vertices in a graph. Due to its large applicability, several graph clustering algorithms have been proposed in the last years. A particular class of graph clustering algorithms is known as spectral clustering algorithms. These algorithms are mostly based on the eigen-decomposition of Laplacian matrices of either weighted or unweighted graphs. This survey presents different graph clustering formulations, most of which based on graph cut and partitioning problems, and describes the main spectral clustering algorithms found in literature that solve these problems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Operational Research - Volume 211, Issue 2, 1 June 2011, Pages 221–231
Journal: European Journal of Operational Research - Volume 211, Issue 2, 1 June 2011, Pages 221–231
نویسندگان
Mariá C.V. Nascimento, André C.P.L.F. de Carvalho,