FRINK Linked Data Fragments server

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• W2533435397 abstract "As an important resource and productive element, big data permeates all the domains, such as: E-commerce, traffic management or smart city. When possessing the capability of aggregating the information and then mining and analyzing deeply the latent knowledge, it will bring endless innovative achievements. Therefore, big data mining and deep analytics is becoming one of the research hotspots, and has attracted more and more attention from academia, industry as well as government. However, because of the 3Vs (volume, velocity and variety) characters of the big data, there is no single tool or a one-size-fits-all solution for big data processing. This paper reports our own experiences in building a cloud-based big data mining & analyzing services platform by integrating R for providing rich data statistical and analytic functions. The architecture of the services platform is discussed in details, which includes four layers: infrastructure layer, virtualization layer, dataset processing layer and services layer. Following the whole architecture, the implementation of K-Means algorithm service is introduced as an example. Finally, we propose the conclusion, and explore the research directions in the future." @default.
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• W2533435397 date "2013-12-01" @default.
• W2533435397 modified "2023-09-27" @default.
• W2533435397 title "Cloud-Based Big Data Mining &amp;amp; Analyzing Services Platform Integrating R" @default.
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• W2533435397 doi "https://doi.org/10.1109/cbd.2013.13" @default.
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