A Semantic-Driven Knowledge Representation Model for the Materials Engineering Application

Data Science Journal

Yang Li¹  Changjun Hu¹  Xin Cheng¹ 

[1] 1) School of Computer and Communication Engineering, University of Science and Technology Beijing 2) Beijing Key Laboratory of Knowledge Engineering for Materials Science;

关键词: Knowledge representation model;    Domain ontology;    Semantic mapping;    Reasoning rule;    Evolution tracking;    Materials engineering application;   

DOI  :  10.2481/dsj.13-061

来源: DOAJ

【 摘 要 】

A Materials Engineering Application (MEA) has been presented as a solution for the problems of materials design, solutions simulation, production and processing, and service evaluation. Large amounts of data are generated in the MEA distributed and heterogeneous environment. As the demand for intelligent engineering information applications increases, the challenge is to effectively organize these complex data and provide timely and accurate on-demand services. In this paper, based on the supporting environment of Open Cloud Services Architecture (OCSA) and Virtual DataSpace (VDS), a new semantic-driven knowledge representation model for MEA information is proposed. Faced with the MEA constantly changing user requirements, this model elaborates the semantic representation of data, services and their relationships to support the construction of domain knowledge ontology. Then, based on the ontology modeling in VDS, the semantic representations of association mapping, rule-based reasoning, and evolution tracking are analyzed to support MEA knowledge acquisition. Finally, an application example of knowledge representation in the field of materials engineering is given to illustrate the proposed model, and some experimental comparisons are discussed for evaluating and verifying the effectiveness of this method.

【 授权许可】

Unknown