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- W2922273584 abstract "Information classification is imperative for machine identification in artificial intelligence. Current information classification approaches only satisfy the mechanization of machines for human services. An essential question is still unresolved, which motivates people to find a way to make machine work for human with thinking. This thesis first discusses information classification in a broad perspective, using a method different from traditional ones which only pay attention to technology and ignore integrity. Then it proposes the three dimension information model of physical entities - information entities - observers. In this paper, we divide information into natural information and social information. And the process of out-structuring information is divided into generalized communication and generalized transmission, which puts forward new ideas for the generalization and systematization of information research." @default.
- W2922273584 created "2019-03-22" @default.
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- W2922273584 date "2019-02-01" @default.
- W2922273584 modified "2023-09-27" @default.
- W2922273584 title "The study on the out-structure information classification based on observers" @default.
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- W2922273584 doi "https://doi.org/10.1088/1742-6596/1168/2/022031" @default.
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