doi: 10.17706/jsw.16.5.200-207
Unknown Oriented Programming: Mathematical Continuation
Abstract—Natural language semantic engineering problems are faced with unknown input and intensive knowledge challenges. In order to adapt to the featuresof natural language semantic engineering, the AI programinglanguage needs to be expanded mathematically: 1) Using many ways to improve the spatial distribution and coverage of instances; 2) Keeping different abstract function versions running at the same time; 3) Providing a large numberof knowledge configuration files and supporting functions to deal with intensive knowledge problems; 4) Using the most possibilitypriority call to solve the problem of multiple running branchestraversal. This paper introduces the unknown oriented programming ideas, basic strategy formulation,language design and simulation running examples. It provides a new method for the incremental research and development of large-scale natural language semantic engineeringapplication. Finally, this paper summarizes the full text and puts forward the further research direction.
Index Terms—Commonsense, humanoid resolving, semantic engineering, unknown oriented programming
Cite: Zhu Ping, "Unknown Oriented Programming: Mathematical Continuation," Journal of Software vol. 16, no. 5, pp. 200-207, 2021.
Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0)
General Information
ISSN: 1796-217X (Online)
Abbreviated Title: J. Softw.
Frequency: Quarterly
APC: 500USD
DOI: 10.17706/JSW
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Cecilia Xie
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