Cited by Lee Sonogan
Abstract by Zhu Ping
Abstract: Natural language semantic engineering problems are faced with unknown input and intensive knowledge challenges. In order to adapt to the features of natural language semantic engineering, the AI programing language needs to be expanded mathematically: 1) Using many ways to improve the spatialdistribution and coverage of instances; 2) Keeping different abstract function versions running at the same time; 3) Providing a large number of knowledge configuration files and supporting functions to deal with intensive knowledge problems; 4) Using the most possibility priority call to solve the problem of multiple running branches traversal. 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 engineering application. Finally, this paper summarizes the full text and puts forward the further research direction.
Publication: Journal Of Software (Peer-Reviewed Journal)
Pub Date: May 11, 2021 Doi: http://www.jsoftware.us/vol16/445-C0003.pdf
Keywords: Commonsense, humanoid resolving, semantic engineering, unknown oriented programming
http://www.jsoftware.us/vol16/445-C0003.pdf (Plenty more sections and references in this research article)