Mining the Web: Transforming Customer Data into Customer Value
Mining the Web: Transforming Customer Data into Customer Value
Retrieval effectiveness of an ontology-based model for information selection
The VLDB Journal — The International Journal on Very Large Data Bases
Verbs semantics and lexical selection
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Measuring semantic similarity in the taxonomy of WordNet
ACSC '05 Proceedings of the Twenty-eighth Australasian conference on Computer Science - Volume 38
Investigating ontology development for engineering design support
Advanced Engineering Informatics
HIS '08 Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems
Expert Systems with Applications: An International Journal
A methodology for engineering ontology acquisition and validation
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Expert Systems with Applications: An International Journal
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Research on Ontology-Based Case Indexing in CBR
AICI '09 Proceedings of the 2009 International Conference on Artificial Intelligence and Computational Intelligence - Volume 04
Research on CBR system based on data mining
Applied Soft Computing
A domain ontology model for mould design automation
AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
Research on an active knowledge push service based on collaborative intent capture
Journal of Network and Computer Applications
Hi-index | 0.00 |
Case-based reasoning (CBR) often shows significant promise for improving the effectiveness of design support in mould design, which is a domain strong in practice but poor in theory. However, existing CBR systems lack semantic understanding, which is important for intelligent knowledge retrieval in design support system. This hinders the application of CBR in injection mould design. In order to develop an intelligent CBR system and meet the need of design support for injection mould design, this paper integrates ontology technology into a CBR system by constructing domain ontology as case-base with a new method, in which two means of acquisition are combined, one is acquiring ontology from existing ontologies, the other from established engineering knowledge resources, and proposing a new semantic retrieval method as the first grade case retrieval. Numerical measurement is also employed as the second grade case retrieval, which adopts various methods to calculate different types of attribute values. A case is executed to illustrate the use of proposed CBR system, then a lot of experiments are organized to evaluate its performance and the result shows that the proposed approach outperforms existing CBR systems.