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CARE: Cloud Archival Repository Express via Algorithmic Machine Learning

Sheldon Liang, Clara Hall, James Pogge, Melanie Van Stry

Abstract: CARE—Cloud Archive Repository Express has emerged from algorithmic machine learning, and acts like a “fastlane” to bridge between DATA and wiseCIO where DATA stands for digital archiving & trans-analytics, and wiseCIO for web-based intelligent service. CARE incorporates DATA and wiseCIO into a triad for content management and delivery (CMD) to orchestrate Anything as a Service (XaaS) by using mathematical and computational solutions to cloud-based problems. This article presents algorithmic machine learning in CARE for “DNA-like” ingredients with trivial information eliminated through deep learning to support integral content management over DATA and informative delivery on wiseCIO. In particular with algorithmic machine learning, CARE creatively incorporates express tokens for information interchange (eTokin) to promote seamless intercommunications among the CMD triad that enables Anything as a Service and empowers ordinary users to be UNIQ professionals: such as ubiquitous manager on content management and delivery, novel designer on universal interface and user-centric experience, intelligent expert for business intelligence, and quinary liaison with XaaS without explicitly coding required. Furthermore, CMD triad harnesses rapid prototyping for user interface design and propels cohesive assembly from Anything orchestrated as a Service. More importantly, CARE collaboratively as a whole promotes instant publishing over DATA, efficient presentation to end-users via wiseCIO, and diligent intelligence for business, education, and entertainment (iBEE) through highly robotic process automation.
Keywords: Algorithmic Machine Learning / Express Token for Information Interchange / Instant Typing Online Publishing / Cloud Archival Repository Express

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