Analysis of Knowledge Fusion System Model Based on Ontology and Multi-Agent Theory

Li Lei; Man Zhang

doi:10.4028/www.scientific.net/AMR.989-994.1505

Paper Titles

A Fuzzy Clustering Algorithm of Automatic Classification Based on EnFCM
p.1489

Knowledge Representation of Art Patterns Based on the Calculation Mental Image
p.1493

Improved Software Cost Estimation Method Based on COCOMO Model and Linear Regression
p.1497

Research on Improved Staged Software Cost Estimation Method Based on COCOMO Model
p.1501

Analysis of Knowledge Fusion System Model Based on Ontology and Multi-Agent Theory
p.1505

Research on Classification and Encoding of Digital Cultural Relics
p.1509

An OCL-Based Formal Model for Cloud Forensics
p.1513

Research on Customers Churn Prediction Model Based on Logistic
p.1517

Site Selection of Customer Operation Center for Pull and Drag Transportation Based on the Analytic Hierarchy Process
p.1522

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 989-994Analysis of Knowledge Fusion System Model Based on...

Analysis of Knowledge Fusion System Model Based on Ontology and Multi-Agent Theory

Abstract:

Information increase rapidly in recent years which make the effective use of information is not that easy. Knowledge fusion can improve the semantic accuracy and specification of knowledge; it’s a useful way to make the mass disordered information integrated and easy to be recognized for users. The paper proposed a knowledge fusion system model based on ontology and multi-agent theory to meet with the user’ changing needs at any time.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 989-994)

Pages:

1505-1508

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.989-994.1505

Citation:

Cite this paper

Online since:

July 2014

Authors:

Li Lei*, Man Zhang

Keywords:

Knowledge Fusion, Multi-Agent, Ontology, System Model

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Chunnian Liu, Yiyun Huang, Yubao Li, el at. Research on Construction and Application of Agricultural Risk Knowledge Based on Ontology. International Journal of Digital Content Technology and its Applications , vol. 6, no. 15, pp.338-346, (2012).

DOI: 10.4156/jdcta.vol6.issue15.38

Google Scholar

[2] Li Jinhua, Jiao Yuying. Research on online information service model and algorithm Based on Intelligent Agent thematic . Intelligence theory and practice, vol. 6, pp.51-54, (2002).

Google Scholar

[3] Preece A.D., Hui K.Y., Gray W.A., et al. The KRAFT Architecture for Knowledge Fusion and Transformation]. Knowledge Based Systems, vol. 13, no. 2, pp.113-120. (2000).

DOI: 10.1016/s0950-7051(00)00052-6

Google Scholar

[4] Zou Xiang-jun. Virtual environment modeling and design of mechanical products based Knowledge Fusion. Guangdong University of Technology , (2005).

Google Scholar

[5] Gou Jin. key technology of knowledge fusion research integration. Zhejiang University, 2005.

Google Scholar

[6] Hu Bei, Wang Congying. High-tech industrial clusters and innovative model for developing coutries based knowledge fusion. Library and Information, vol. 2, pp.38-41 +73, (2009).

Google Scholar

[7] Zhou Fang, Wang Pengbo, Han Liyan. Research on multi-source information integration algorithm . Journal of Beijing University of Aeronautics and Astronautics , vol. 01, pp.109-114, (2013).

Google Scholar

[8] Cheng Quan. Community knowledge fusion mechanism research based on collaborative tagging . Intelligence theory and practice , vol. 8, pp.20-25, (2011).

Google Scholar

[9] Ji Cheng, Zhu Xiaoming. Knowledge fusion based knowledge integration management of Enterprise mergers and acquisition. Research and development management , vol. 6, pp.78-84, (2007).

Google Scholar