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Tepper's declaration of 2011 SME Technology Innovation Fund projects approved by

From the good news Science and Technology Bureau, Guangzhou Tepper software company declared 2011 the Year SME Technology Innovation Fund "Cloud computing and SOA architecture based on massive data mining platform," after several rounds of expert review and, ultimately, approval by .

The project is based on the cloud-based computing technology, data mining applications, the company's many years of experience in data mining summarizes the new generation of systems, systems required to support data mining tasks in the primary process, and provide an open application interface and commonly used algorithms, to meet complex business intelligence applications. System has been used in agriculture, electricity, telecommunications and education sectors, and promote applications in government, finance, insurance, manufacturing, life sciences and other industries, we can say, as long as the analysis of the value of enterprise data sources with may apply to use the system for high performance of data mining analysis. The main features of the system and the innovation are:
System uses cloud computing technology to achieve efficient processing of massive data mining; using SOA architecture enables scalability of the platform greatly enhanced, and other business systems can be efficiently integrated; data pre-processing stage using wavelet transform, to provide a new anomaly detection perspective; using PCA, LDA, ICA and other feature extraction methods and theory of compressed sensing to achieve efficient data compression; adaptive and self-learning prediction strategy to complete the model structure and parameters automatically adjusted and optimized.
标签: application interface, technology innovation, computing technology, model structure, self learning, massive data, applications system, data compression, anomaly detection, technology bureau, open application, technology data, business intelligence applications, government finance, innovation fund, fund projects, feature extraction methods, education sectors, finance insurance, news science
分类: Industry
时间: 2011-08-20

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