An informative graph, directed or undirected, is critical for those graph-orientated algorithms designed for data analysis, such as clustering, subspace learning, and semi-supervised learning. Data clustering often starts with a pairwise similarity graph and then translates into a graph partition problem , and thus the quality of the graph essentially determines the clustering quality.
|Original language||English (US)|
|Title of host publication||Graph Embedding for Pattern Analysis|
|Number of pages||18|
|State||Published - Jan 1 2013|
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