期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2016
卷号：9
期号：4
页码：417-426
DOI：10.14257/ijhit.2016.9.4.36
出版社：SERSC
摘要：Spectral clustering is a method of subspace clustering which is suitable for the data of any shape and converges to global optimal solution. By combining concepts of shared nearest neighbors and geodesic distance with spectral clustering, a self-adaptive spectral clustering based on geodesic distance and shared nearest neighbors was proposed. Experiments show that the improved spectral clustering algorithm can fully take into account the information of neighbors, but also measure the exact distance and better process the geodetic data.
