Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

A Large-Scale Ontology Mapping Method for Chinese Language

An ontology mapping, large-scale technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of lack, large heterogeneity, low efficiency, etc.

Inactive Publication Date: 2018-02-02
CAPITAL UNIV OF ECONOMICS & BUSINESS
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0013] Therefore, there are still few Chinese large-scale ontology published on the web, and there is a large heterogeneity, and the existing Chinese ontology mapping system is inefficient and unavailable when facing large-scale ontology mapping tasks. high
At the same time, there is still a lack of related systems for Chinese language descriptions that are suitable for large-scale ontology mapping tasks in the semantic web environment

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 Large-Scale Ontology Mapping Method for Chinese Language
  • A Large-Scale Ontology Mapping Method for Chinese Language
  • A Large-Scale Ontology Mapping Method for Chinese Language

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0073] (1) Calculation of concept initial correlation based on edit distance and synonym Cilin fusion

[0074] a) Edit distance similarity

[0075] When faced with the task of mapping a large-scale ontology, the present invention proposes to compress the ontology to be mapped first. Specifically, the edit distance algorithm is used to calculate the initial similarity between concept sets. This is because the efficiency of the algorithm is often considered when calculating the initial correlation degree, while its accuracy is regarded as a secondary factor.

[0076] That is to say, when obtaining the initial correlation degree of the ontology to be mapped, the system can obtain the literal similarity between concepts through the edit distance algorithm, while ignoring their semantic correlation. Especially for two concepts C source and C target , their edit distance values ​​and their similarity values ​​can be described by formula (1) and formula (2):

[0077]

[0078]...

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 invention provides a large-scale Chinese ontology-oriented mapping method. The method includes: a concept initial correlation degree calculation method based on the fusion of synonyms and edit distance similarity algorithms; a quasi-nuclear force field potential function based on the improved fusion of concept similarity and dissimilarity based on the initial correlation degree. Compress the scale of large-scale ontology mapping; measure the similarity of complex concepts in Chinese ontology by introducing a global sequence alignment algorithm. Due to the phenomenon of polysemy and word order sensitivity in Chinese words, and the computational overhead of large-scale ontology mapping is very large, and the present invention first improves the existing quasi-nuclear force field potential function so that the measurement of the similarity between concepts and the to-be-mapped Ontology scale reduction is more reasonable. Secondly, the global sequence alignment technology is used to map complex Chinese concepts, and then improve the defects of the existing Chinese ontology mapping system, and finally improve the mapping efficiency, precision and recall of the system.

Description

technical field [0001] The invention relates to the field of Chinese ontology mapping. Background technique [0002] The vision of the Semantic Web is to build a "Web of Data" (Web of Data) to enable machines to understand semantic information on the Web. Ontology, as the core element of Semantic Web, is a formalized and standardized description to describe shared concepts in a specific field, and is the basis for realizing network knowledge sharing and semantic interoperability. At present, due to the heterogeneity among different ontologies, it becomes difficult to reuse and share between ontologies. [0003] The task of ontology alignment (Ontology Alignment) is to discover the conceptual semantic association between heterogeneous ontologies. However, due to cultural and background reasons, there is still a lack of a mature ontology mapping system for Chinese language description. With the development of the Semantic Web, large-scale ontology and knowledge bases descri...

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): G06F17/30G06F17/27
Inventor 王汀刘经纬蔡万江
Owner CAPITAL UNIV OF ECONOMICS & BUSINESS
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
Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com