Wang Pei-zhuang, Zeng Fan-hui, Sun Hui, et al. Extension of Knowledge Graph and its Intelligent Extension Library[J]. 2021, 38(4): 9-16.DOI: 10.12052/gdutxb.210045.
Extension of Knowledge Graph and its Intelligent Extension Library
The ultimate goal of constructing the database of the knowledge graph should be the isomorphism of human brain knowledge growth
and it should not be a passive solidified storage body but an actively growing hatching body. The idea of intelligent reproduction library is proposed
which is an updated version of the Knowledge graph
a multi-level embedded graph database system. Each concept node is a window. Open the window
and there is a sub-library produced. All concepts are coded hierarchically for fast query. A concept node is called a bud if the concept has multiple factors taking it as domain. Open the window of the bud
and a cause and effect analysis table is prepared
on which
factor space theory can perform algorithms to make intelligent judgment
reasoning
evaluation
decision-making and planning
by which the database becomes a living intelligent incubator. The Factorial Query Language (FQL) is also established
which may be used in the preparation of the intelligent incubation civil intelligent engineering
with guidance of the mechanistic general artificial intelligence theory.
LIU Q, LI Y, DUAN H, et al . Knowledge graph construction techniques [J ] . Journal of Computer Research and Development, 2016, 53(3): 582-600.
HIBA A, SHADY E. Effective searching of RDF knowledge graphs [J]. Web Semantics: Science, Services and Agents on the World Wide Web, 2018(48): 66-84.
CAI W, YANG C Y. Basic theory and method system of topology [J]. Chinese Science Bulletin, 2013, 58(13): 1190-1199.
LI X S, XU L B, LIU H T. A research on problem oriented intelligent processing model by basic-element and factor space [J]. Journal of Guangdong University of Technology, 2019, 36(1): 1-9.
WILLE R. Restructuring lattice theory: an approach based on hierarchies of concepts [J]. Ordered Set, 1982: 445-470.
PAWLAK Z. Rough sets [J]. International Journal of Computer and Information Sciences, 1982, 11(5): 341-356.
汪培庄, 李洪兴. 知识表示的数学理论[M]. 天津: 天津科技出版社, 1994.
WANG P Z, SUGENO M. The factors field and background structure for fuzzy subsets [J]. Fuzzy Math, 1982, 2(2): 45-54.
汪培庄. 模糊集与随机集落影[M]. 北京: 北京师范大学出版社, 1985.
REN S H, ZENG F H, GUO S Z. Fuzzy markov decision process based on structural element theory [J]. Journal of Liaoning Technical University (Natural Science), 2020, 39(2): 180-183.
PU L J, ZENG F H, WANG P Z. Base point classification algorithm based on factor space theory [J]. CAAI Transactions on Intelligent Systems, 2020, 15(3): 528-536.
SUN H, ZENG F H, PU L J. Research on dimension reduction algorithm of multiple targets causal analysis based on factor space theory [J]. Journal of Liaoning Technical University (Natural Science), 2021, 40(5): 466-472.