Knowledge Modeling and Semantic Retrieval of Product Data Based on Fuzzy Ontology and SPARQL

2011 ◽  
Vol 4 (4) ◽  
pp. 1855-1859 ◽  
Author(s):  
Jun Zhai ◽  
Changfeng Yuan ◽  
Yan Chen ◽  
Jianfeng Li
Keyword(s):  
Semantic Retrieval ◽  
Knowledge Modeling ◽  
Product Data ◽  
Fuzzy Ontology

Knowledge Modeling of Product Data Based on Fuzzy Ontology

2010 ◽  
Vol 26-28 ◽  
pp. 347-351 ◽  
Author(s):  
Jun Zhai ◽  
Jian Feng Li ◽  
Yan Chen
Keyword(s):  
Semantic Web ◽  
Knowledge Sharing ◽  
Domain Ontology ◽  
Product Data Management ◽  
Product Knowledge ◽  
Knowledge Modeling ◽  
Product Data ◽  
Fuzzy Ontology ◽  
Fuzzy Linguistic Variable ◽  
Fuzzy Linguistic

Ontology is the basis of knowledge modeling on the Semantic Web, and fuzzy ontology is an extension of domain ontology for solving the uncertainty problems. Ontology-base knowledge modeling of product data management (PDM) is meaningful for product design and trade etc. In order to handle fuzzy phenomenon and uncertainty of product knowledge, this paper proposes a series of fuzzy ontology models that consists of fuzzy domain ontology and fuzzy linguistic variable ontologies. Then, a fuzzy ontology framework is presented, including three parts: concepts, properties of concepts and values of properties. The application, which uses fuzzy ontology to model product knowledge, shows that these models can overcome the localization of other fuzzy ontology models, and this research facilitates the fuzzy knowledge sharing and reuse for PDM on the Semantic Web.

An Ontology-Based Online Community to Maintain Engineering Knowledge in a Training Domain

2011 ◽  
Author(s):  
OkJoon Kim ◽  
Uma Jayaram ◽  
Lijuan Zhu
Keyword(s):  
Engineering Design ◽  
Online Community ◽  
Procedural Knowledge ◽  
Knowledge Exchange ◽  
Knowledge Modeling ◽  
Product Data ◽  
Engineering Knowledge ◽  
Knowledge Presentation ◽  
On Line ◽  
And Training

The research presented in this paper seeks to develop an ontology-based online community for knowledge exchange between expert engineers and new engineers. We call this community CREEK (Community for Retention of Engineering dEsign Knowledge). This paper seeks to develop methods and tools related to knowledge acquisition, knowledge modeling, knowledge management, and knowledge presentation that can support activities in this community in engineering design and training domains. An important consideration is to design and deploy the online community and the underlying ontology model such that they will not exist in isolation but will be connected to a product data ontology and a training ontology. In our previous work engineering knowledge related to product data in engineering design and assembly has been modeled. In this work procedural knowledge and knowledge in the training domains related to these procedures are also modeled and populated using ontologies. We have designed an architecture that will allow the ontology of the on-line community to tap into the engineering knowledge from these two supporting domains. In addition, there is a connection the other way too. The online community also allows new knowledge to be captured from experts and be (semi-)automatically transferred to product design and training domains.

Review of Computer Aided Product Innovation Design Based on Knowledge

2015 ◽  
Vol 713-715 ◽  
pp. 2335-2340 ◽  
Author(s):  
Ji Wen Chen ◽  
Xiao Dong Xu ◽  
Xiao Qin Shen
Keyword(s):  
Product Innovation ◽  
Design Knowledge ◽  
Semantic Retrieval ◽  
Knowledge Modeling ◽  
Core Competitiveness ◽  
Concept Hierarchy ◽  
Semantic Relationships ◽  
Manufacturing Enterprises ◽  
Key Technologies ◽  
Computer Aided

Design knowledge acquisition, representation and application are key technologies in computer-aided innovation design. It is an important way to improve the innovation capability and core competitiveness of manufacturing enterprises. The present state of the art of theories and tools of computer-aided product innovation design was presented, some key technologies and problems of the computer-aided product innovation design based on knowledge were summarized and analyzed. It was proposed that the ontology-based knowledge modeling based on design process was the base of computer-aided innovation design, The efficient and precise ontology matching method is seeked to efficiently support updating design knowledge by synthetically considering the concept semantics and concept hierarchy structure, and the knowledge association and concept semantic retrieval and reasoning can be better realized by taking into full consideration of semantic relationships of between design knowledges.

Fuzzy Semantic Retrieval for Traffic Information Based on Fuzzy Ontology and RDF on the Semantic Web

2009 ◽  
Vol 4 (7) ◽  
Author(s):  
Jun Zhai ◽  
Yan Chen ◽  
Yi Yu ◽  
Yiduo Liang ◽  
Jiatao Jiang
Keyword(s):  
Semantic Web ◽  
Traffic Information ◽  
Semantic Retrieval ◽  
Fuzzy Ontology

Knowledge Modeling and Semantic Retrieval for Sports Information Based on Ontology

2011 ◽  
Vol 187 ◽  
pp. 45-50
Author(s):  
Jun Zhai ◽  
Meng Li ◽  
Pan Sun
Keyword(s):  
Retrieval System ◽  
Query Language ◽  
Practical Significance ◽  
Semantic Retrieval ◽  
Knowledge Modeling ◽  
Information Granularity ◽  
Semantic Level ◽  
Concept Hierarchy ◽  
Sports Information ◽  
Logic Reasoning

Ontology, with the excellent concept hierarchy and appropriately supporting for logic reasoning, is the basis of knowledge modeling on the Semantic Web and the effective tool for semantic retrieval. This paper pays attention to the sports information management in WWW. Firstly, based on the domain ontology model, we build the sports ontology which has the character of wide-cover and small information granularity. Then this paper present the semantic retrieval system for sports information using SPARQL query language, which realizes the intelligent retrieval at semantic level according to the relations of “synonymy of”, “kind of” and “part of” between sports concepts. For the trend of exploding increase of sports information, this research has practical significance to some extent.

scholarly journals Knowledge Modeling of Airborne Missile Management System Based on Multi-dimensional Fuzzy Ontology

2021 ◽  
Vol 1952 (4) ◽  
pp. 042073
Author(s):  
Jianfeng Li ◽  
Mingqing Xiao ◽  
Yao Sun ◽  
Yaojun Chen
Keyword(s):  
Management System ◽  
Knowledge Modeling ◽  
Fuzzy Ontology

Detection Algorithm of Semantic Inconsistency for Fuzzy Ontology Merging

2014 ◽  
Vol 530-531 ◽  
pp. 407-412
Author(s):  
Yong Hong Luo ◽  
Wei Ming Liu
Keyword(s):  
Domain Knowledge ◽  
Heterogeneous Systems ◽  
Detection Algorithm ◽  
Semantic Integration ◽  
Detection Methods ◽  
Knowledge Modeling ◽  
Distributed Environment ◽  
Ontology Merging ◽  
Fuzzy Ontology ◽  
Multiple Data

Fuzzy ontology can be built to effectively deal with uncertainty and ambiguity for domain knowledge modeling. Merging multiple fuzzy local ontologies may implement semantic integration of multiple data sources and semantic interoperability between heterogeneous systems in distributed environment. In order to solve the problem of semantic inconsistency mappings for fuzzy ontology merging system, we proposed a detection algorithm of semantic inconsistency mapping which includes sub detection methods of circular semantic inconsistency, subclass-of axiom redundancy semantic inconsistency, attribute membership semantic inconsistency and disjoint axioms redundancy semantic inconsistency. With the detection algorithm of semantic inconsistency, we establish fuzzy ontology merging system in experiment.

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