Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Feature-based similarity assessment of solid models
SMA '97 Proceedings of the fourth ACM symposium on Solid modeling and applications
Resolving non-uniqueness in design feature histories
Proceedings of the fifth ACM symposium on Solid modeling and applications
Database techniques for archival of solid models
Proceedings of the sixth ACM symposium on Solid modeling and applications
A discourse on geometric feature recognition from CAD models
Journal of Computing and Information Science in Engineering
Topology matching for fully automatic similarity estimation of 3D shapes
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Machine Learning
Using shape distributions to compare solid models
Proceedings of the seventh ACM symposium on Solid modeling and applications
ACM Transactions on Graphics (TOG)
Machining Feature-Based Comparisons of Mechanical Parts
SMI '01 Proceedings of the International Conference on Shape Modeling & Applications
A deployed engineering design retrieval system using neural networks
IEEE Transactions on Neural Networks
Benchmarking CAD search techniques
Proceedings of the 2005 ACM symposium on Solid and physical modeling
Feature-based similarity search in 3D object databases
ACM Computing Surveys (CSUR)
A new 3D model retrieval approach based on the elevation descriptor
Pattern Recognition
A 3D object classifier for discriminating manufacturing processes
Computers and Graphics
A boosting approach to content-based 3D model retrieval
Proceedings of the 5th international conference on Computer graphics and interactive techniques in Australia and Southeast Asia
A survey of content based 3D shape retrieval methods
Multimedia Tools and Applications
A 3D model retrieval approach using the interior and exterior 3D shape information
Multimedia Tools and Applications
Three-dimensional shape searching: state-of-the-art review and future trends
Computer-Aided Design
Matching 2D and 3D articulated shapes using the eccentricity transform
Computer Vision and Image Understanding
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This paper describes a new approach to automate the classification of solid models using machine learning techniques. Existing approaches, based on group technology, fixed matching algorithms or pre-defined feature sets, impose a priori categorization schemes on engineering data or require significant human labeling of design data. This paper describes a shape learning algorithm and a general technique for "teaching" the algorithm to identify new or hidden classifications that are relevant in many engineering applications. In this way, the core shape learning algorithm can be used to find a wide variety of model classifications based on user input and training data. This allows for great flexibility in search and data mining of engineering data.