Abstract
Biologically inspired design (BID) is a methodology for designing technological systems by analogy to designs of biological systems. Given that knowledge of many biological systems is available mostly in the form of textual documents, the question becomes how can we extract design knowledge about biological systems from textual documents for potential use in designing engineering systems? In earlier work, we described how annotating biology articles with partial Structure-Behavior-Function models helps users access documents relevant to a given design problem and understand the biological systems for potential transfer of their causal mechanisms to engineering problems. In this paper, we present an automated technique instantiated in the IBID system for extracting partial SBF models of biological systems from their natural language documents for potential use in biologically inspired design.
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Acknowledgements
We are grateful to Julian Vincent for sharing his ontology for describing biological systems (Vincent 2014); IBID uses Vincent’s ontology of biological components and connections. We also wish to acknowledge the contributions of Arvind Jaganathan, Nilesh More, and Sanjana Oulkar to the development of IBID.
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Rugaber, S. et al. (2016). Knowledge Extraction and Annotation for Cross-Domain Textual Case-Based Reasoning in Biologically Inspired Design. In: Goel, A., DÃaz-Agudo, M., Roth-Berghofer, T. (eds) Case-Based Reasoning Research and Development. ICCBR 2016. Lecture Notes in Computer Science(), vol 9969. Springer, Cham. https://doi.org/10.1007/978-3-319-47096-2_23
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