Method for finding path relationship of graph based on multiple agent routes

A discovery method, multi-agent technology, applied in the field of associative information mining

Inactive Publication Date: 2012-06-20
ZHEJIANG UNIV
View PDF4 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0012] The present invention aims at computing problems that require large-scale relational data, overcomes the shortcoming that it is diffic

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
  • Method for finding path relationship of graph based on multiple agent routes
  • Method for finding path relationship of graph based on multiple agent routes
  • Method for finding path relationship of graph based on multiple agent routes

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0030] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0031] 1) Implementation framework of graph path relationship discovery method based on multi-agent routing

[0032] First, use the Resource Description Framework (RDF) and the semantic extraction and editing tool Protégé to obtain semantic relationship graphs from each knowledge domain, that is, express the semantic knowledge of the domain through semantic triples (s, p, o), and It is not just textual knowledge that cannot be understood by machines, where s represents the subject, p represents the attribute relationship, and o represents the object constrained by the subject through the attribute relationship, which is used as the underlying knowledge base for association relationship discovery. Such as figure 1 As shown, the overall architecture of the present invention consists of a master agent and sub-agent groups controlled by the master...

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 discloses a method for finding a path relationship of a graph based on multiple agent routes. The method comprises the following steps of: firstly, respectively acquiring a semantic relationship graph from each knowledge field by using resource description language and a semantic extracting and editing tool based on W3C standard and taking the semantic relationship graph as a bottom-layer knowledge base for finding the correlation relationship; secondly, constructing a multi-agent distributed route framework through a main agent and a plurality of subagents; thirdly, providing a user interaction interface; fourthly, receiving a hypothesis command of a user and then distributing the hypothesis command to subagent groups for executing a query task by the main agent; and fifthly, receiving the query task and then carrying out route query on a correlation relationship path of the bottom layer knowledge base by the subagent groups and feeding back answers to the user by the main agent after the route query is ended. The method has the advantages that a similar vertex incidence matrix with a weight is established between knowledge from every two different fields; and a distributed route support for querying and demonstrating the interdisciplinary knowledge and the like are provided by adopting a multi-agent technology.

Description

technical field [0001] The invention relates to semantic web technology, data mining technology, graph theory application and intelligent agent technology, and in particular relates to associated information mining of multi-agent technology on large-scale semantic graph. Background technique [0002] 1. Semantic Web Technology [0003] The core of the Semantic Web is to make the entire Internet a general information exchange medium by adding semantics that can be understood by computers to documents on the World Wide Web. The Semantic Web extends the capabilities of the Web through the use of standards, markup languages, and related processing tools. The so-called "semantics" is the meaning of the text, and the Semantic Web is a network that can judge according to the semantics, that is, a network that can understand human language, and can make the communication between people and computers as easy as the communication between people. smart network. [0004] In addition ...

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
IPC IPC(8): G06F17/27
Inventor 顾珮嵚王超陈华钧
Owner ZHEJIANG UNIV
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