期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2017
卷号：5
期号：6
页码：11666
DOI：10.15680/IJIRCCE.2017.0506117
出版社：S&S Publications
摘要：Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. Withthe fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expandingin all science and engineering domains, including physical, biological and biomedical sciences. With Big Datatechnologies, we will hopefully be able to provide most relevant and most accurate social sensing feedback to betterunderstand our society at real time. Those data on the Internet exist in vast scale and grow rapidly, so it is urgentlyrequired in technology to mine high-value information from the mass data. This paper introduces an efficient parallelspectral clustering algorithm. The experimental results show that the proposed parallel spectral clustering algorithm issuitable for applying in mass data mining.
