Publication
Automatic Extraction of Causally Related Functions from Natural-Language Text for Biomimetic Design
AbstractIdentifying relevant analogies from biology is a significant challenge in biomimetic design. Our natural-language approach addresses this challenge by developing techniques to search biological information in natural-language format, such as books or papers. This paper presents the application of natural-language processing techniques, such as part-of-speech tags, typed-dependency parsing, and syntactic patterns, to automatically extract and categorize causally related functions from text with biological information. Causally related functions, which specify how one action is enabled by another action, are considered important for both knowledge representation used to model biological information and analogical transfer of biological information performed by designers. An extraction algorithm was developed and scored F-measures of 0.78–0.85 in an initial development test. Because this research approach uses inexpensive and domain-independent techniques, the extraction algorithm has the potential to automatically identify patterns of causally related functions from a large amount of text that contains either biological or design information.
Download publicationRelated Resources
See what’s new.
2023
Research Conversations with Stefanie PenderSenior Shop Supervisor Stefanie Pender talks about working with robots…
2009
A Survey of Software Learnability: Metrics, Methodologies and GuidelinesIt is well-accepted that learnability is an important aspect of…
2020
A subtractive manufacturing constraint for level set topology optimizationWe present a method for enforcing manufacturability constraints in…
2014
Wasserstein propagation for semi-supervised learningProbability distributions and histograms are natural representations…
Get in touch
Something pique your interest? Get in touch if you’d like to learn more about Autodesk Research, our projects, people, and potential collaboration opportunities.
Contact us