Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
A relational model of data for large shared data banks
Communications of the ACM
E-Learning: Strategies for Delivering Knowledge in the Digital Age
E-Learning: Strategies for Delivering Knowledge in the Digital Age
Designing and Evaluating E-Business Models
IEEE Intelligent Systems
Towards a general ontology of configuration
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
AICT-SAPIR-ELETE '05 Proceedings of the Advanced Industrial Conference on Telecommunications/Service Assurance with Partial and Intermittent Resources Conference/E-Learning on Telecommunications Workshop
Mining Ontology for Automatically Acquiring Web User Information Needs
IEEE Transactions on Knowledge and Data Engineering
SNPD-SAWN '06 Proceedings of the Seventh ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Information retrieval at Boeing: plans and successes
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Top 10 algorithms in data mining
Knowledge and Information Systems
Knowledge reuse in manufacturability analysis
Robotics and Computer-Integrated Manufacturing
O2DSS: A Framework for Ontology-Based Decision Support Systems in Pervasive Computing Environment
AMS '08 Proceedings of the 2008 Second Asia International Conference on Modelling & Simulation (AMS)
A data mining approach to dynamic multiple responses in Taguchi experimental design
Expert Systems with Applications: An International Journal
Education for innovation: trends, collaborations and views
Journal of Intelligent Manufacturing
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This paper identifies how ontology models can be vigorously used to define semantics and relationships in representing objects/modules for e-learning, business modeling support and manufacturing processing details. Further extraction of these relations by intelligent decision-support systems using data mining as a tool is discussed. The paper envisages the possibility of establishing a common solution platform for product development and customization leading to increased profitability and better resource utilization. It showcases ways to link these different ontological models leading to cross platform compatibility. It also tries to explore manufacturer-customer relationship and using them to provide quality analysis methods for further improvement in the product processing model.