کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
533556 870133 2011 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Automatically finding clusters in normalized cuts
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Automatically finding clusters in normalized cuts
چکیده انگلیسی

Normalized Cuts is a state-of-the-art spectral method for clustering. By applying spectral techniques, the data becomes easier to cluster and then k-means is classically used. Unfortunately the number of clusters must be manually set and it is very sensitive to initialization. Moreover, k-means tends to split large clusters, to merge small clusters, and to favor convex-shaped clusters. In this work we present a new clustering method which is parameterless, independent from the original data dimensionality and from the shape of the clusters. It only takes into account inter-point distances and it has no random steps. The combination of the proposed method with normalized cuts proved successful in our experiments.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 44, Issue 7, July 2011, Pages 1372–1386
نویسندگان
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