Research On The Analytical Method Of Network Data

With the explosive growth of data, we have entered the era of big data.How to dig out valuable information from these data sources has become one of the hottest topics in the fields of industry and academy. The network data is an important form of data. Usually data collected from various complex systems is isolated. The links which contain implied relationship between data are in-tegrated to form a complex network. Therefore, the analysis of network is an approach of understanding the intrinsic value of big data.In the second chapter we review that the heuristic community detection method of complex network in the second chapter. Also we aim at the max-imization and parameter selection of the new modularity with neighborhood information, then we reformulate the maximization as a spectral relaxation is sue. Finally, we solve the problem by a new bisection spectral algorithm and prove the effectiveness of our algorithm by experimental results.Further, to study the nature and formation mechanism of the large scale network structure, we must first implement data collection of real network. Then we can verify the effectiveness of the algorithm. The distributed computing is a fast and efficient data processing framework, so implementation of data process-ing based on distributed computing framework is very necessary and important. In the third chapter, we achieve collection of data from the web and complete data cleaning fastly and efficiently based on Spark.