Finding clusters with widely differing sizes, shapes and densities in presence of noise and outliers is a challenging job. The DBSCAN is a versatile clustering algorithm that can f...
In this paper, we present a local, adaptive optimization scheme for adjusting the number of clusters in fuzzy C-means clustering. This method is especially motivated by online app...
Due to resource constraints, search engines usually have difficulties keeping the local database completely synchronized with the Web. To detect as many changes as possible, the ...
Qingzhao Tan, Ziming Zhuang, Prasenjit Mitra, C. L...
Understanding high-dimensional real world data usually requires learning the structure of the data space. The structure maycontain high-dimensional clusters that are related in co...
Background: In recent years protein structure prediction methods using local structure information have shown promising improvements. The quality of new fold predictions has risen...