Biology is a good source of analogies for engineering design. One approach of retrieving biological analogies is to perform keyword searches on natural-language sources such as books, journals, etc. A challenge in retrieving information from natural-language sources is the potential requirement to process a large number of search results. This thesis describes two methods on improving the relevancy of the search results. The first method is inserting metadata such as part- of-speech, word sense and lexicographical data for each word in a natural-language. The second method is categorizing the search results, using WordNet relationships and Wikipedia structures as ontologies. Although this research is still exploratory, initial qualitative observations demonstrate successful identification and separation of biological phenomena relevant to either desired functions or desired qualities. The benefits of embedding metadata are demonstrated through a case study on the redesign of a fuel cell bipolar plate. A prototype was constructed with ability to passively prevent prolonged catastrophic flooding.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/25723 |
| Date | 06 January 2011 |
| Creators | Ke, Ji |
| Contributors | Shu, Lily H., Wallace, James S. |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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