A New Self-Adapting Knowledge Fusion System

Author

Gou, Jin ; Jiang, Yunliang ; Wu, Yangyang ; Luo, Wei

Author_Institution

Huaqiao Univ., Quanzhou

Volume

3

fYear

2007

fDate

24-27 Aug. 2007

Firstpage

454

Lastpage

458

Abstract

This paper presents a new knowledge fusion method with a feedback and self-adapting mechanism. Representing structure of distributed knowledge objects is uniformed by ontology technology and meta-knowledge. A detailed improved knowledge fusion algorithm based on genetic algorithm and semantic filter is described. The proposed feedback mechanism is based on message communication between knowledge space and application service, which can evaluate the fusion results and optimize the fusion process to adapt to the requirements. Experimental results of emulator procedures show the validity and feasibility of design rationale.

Keywords

distributed processing; filtering theory; genetic algorithms; ontologies (artificial intelligence); application service; distributed knowledge objects; feedback; genetic algorithm; knowledge space; message communication; meta-knowledge; ontology; self-adapting knowledge fusion system; semantic filter; Communication system control; Educational institutions; Feedback; Filters; Genetic algorithms; Information science; Knowledge engineering; Knowledge management; Ontologies; Space technology;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on

Conference_Location

Haikou

Print_ISBN

978-0-7695-2874-8

Type

conf

DOI

10.1109/FSKD.2007.89

Filename

4406279