A self-learning method based on 6w knowledge representation

A self-learning method and knowledge representation technology, applied in knowledge representation and other directions, can solve problems such as limited capacity expansion and hindering the construction of intelligent and intelligent systems.

Active Publication Date: 2018-04-20
KARAMAY HONGYOU SOFTWARE
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the existing technology, the expansion capacity of standard knowledge is limited, which hinders the construction of intelligent intelligent system

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A self-learning method based on 6w knowledge representation
  • A self-learning method based on 6w knowledge representation
  • A self-learning method based on 6w knowledge representation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0086] The present invention is described in detail below in conjunction with accompanying drawing:

[0087] The present invention provides a self-learning method based on 6W knowledge representation. The 6W principle originally refers to the "6W principle" of thinking and solving problems of British writer Kipling, a Nobel Prize winner in literature. On this basis, it is clarified Business logic 6W describes the method, that is, "Where (where), When (when), Who (who), Which (for what), What (what is done, including how to do it), Why (why)".

[0088] Since data is associated into information, information is associated into knowledge, and knowledge is associated into wisdom, data, information, and knowledge can be solidified with concepts, knowledge can be understood as the connection between concepts, and concepts are uniquely identified by semantics. In the knowledge system, the Concepts are expressed with symbols; connections are marked with symbols. Identification and lab...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The present invention provides a self-learning method based on 6W knowledge representation, including the following steps: define the identification structure of each concept; define the label structure used to describe the relationship between concepts; define the knowledge code used to describe knowledge; define Knowledge credibility rules for evaluating knowledge credibility to obtain knowledge credibility; define a knowledge structure organization model; wherein, the knowledge structure organization model consists of the identification code, the label code, the knowledge code and The knowledge credibility is combined; knowledge self-learning is performed based on the knowledge structure organization model. The self-learning method based on 6W knowledge representation provided by the present invention, by defining the identification structure, labeling structure and knowledge structure respectively, and then based on the defined labeling structure, labeling structure and knowledge structure, quickly and efficiently expands knowledge, which is beneficial to the intelligent wisdom system building.

Description

technical field [0001] The invention belongs to the technical field of information processing, and in particular relates to a self-learning method based on 6W knowledge representation. Background technique [0002] The construction of intelligent intelligence system will be the theme of the future. The foundation of intelligent intelligence system construction is knowledge, and the amount of knowledge possessed by intelligent intelligence system directly affects the performance of intelligent intelligence system. In the existing technology, the quantity expansion ability of standard knowledge is limited, which hinders the construction of intelligent intelligent system. Contents of the invention [0003] Aiming at the defects in the prior art, the present invention provides a self-learning method based on 6W knowledge representation, which can effectively solve the above problems. [0004] The technical scheme that the present invention adopts is as follows: [0005] The ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G06N5/02
Inventor 夏冬梅
Owner KARAMAY HONGYOU SOFTWARE
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap