SUPPORTING BIOMIMETIC DESIGN BY EMBEDDING METADATA IN NATURAL-LANGUAGE CORPORA

摘要

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 paper describes how inserting metadata such as part-of-speech, word sense and lexicographical data for each word in a natural-language source can help users identify relevant biological stimuli for biomimetic design. 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. In addition, by incorporating the aforementioned metadata, we can automatically remove search results where search keywords act on abstract nouns or where keywords are used in irrelevant senses. The benefits of embedding metadata are demonstrated through a case study on the redesign of a fuel cell bipolar plate. In this case study, our method can be used to hide 64% of the search results that are unlikely to contain useful biological phenomena, reducing the effort to systematically identify relevant biological analogies.