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http://dx.doi.org/10.9708/jksci.2020.25.05.027

Research of Semantic Considered Tree Mining Method for an Intelligent Knowledge-Services Platform  

Paik, Juryon (Dept. of Digital Information and Statistics, Pyeongtaek University)
Abstract
In this paper, we propose a method to derive valuable but hidden infromation from the data which is the core foundation in the 4th Industrial Revolution to pursue knowledge-based service fusion. The hyper-connected societies characterized by IoT inevitably produce big data, and with the data in order to derive optimal services for trouble situations it is first processed by discovering valuable information. A data-centric IoT platform is a platform to collect, store, manage, and integrate the data from variable devices, which is actually a type of middleware platforms. Its purpose is to provide suitable solutions for challenged problems after processing and analyzing the data, that depends on efficient and accurate algorithms performing the work of data analysis. To this end, we propose specially designed structures to store IoT data without losing the semantics and provide algorithms to discover the useful information with several definitions and proofs to show the soundness.
Keywords
Knowledge-based platform; Unstructured data; Tree data; Bits representation; Binary code; Pairsets;
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