Computer-Aided Biomimetics : Semi-Open Relation Extraction from scientific biological texts
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Engineering inspired by biology – recently termed biom* – has led to various groundbreaking technological developments. Example areas of application include aerospace engineering and robotics. However, biom* is not always successful and only sporadically applied in industry. The reason is that a systematic approach to biom* remains at large, despite the existence of a plethora of methods and design tools. In recent years computational tools have been proposed as well, which can potentially support a systematic integration of relevant biological knowledge during biom*. However, these so-called Computer-Aided Biom* (CAB) tools have not been able to fill all the gaps in the biom* process. This thesis investigates why existing CAB tools fail, proposes a novel approach – based on Information Extraction – and develops a proof-of-concept for a CAB tool that does enable a systematic approach to biom*. Key contributions include: 1) a disquisition of existing tools guides the selection of a strategy for systematic CAB, 2) a dataset of 1,500 manually-annotated sentences, 3) a novel Information Extraction approach that combines the outputs from a supervised Relation Extraction system and an existing Open Information Extraction system. The implemented exploratory approach indicates that it is possible to extract a focused selection of relations from scientific texts with reasonable accuracy, without imposing limitations on the types of information extracted. Furthermore, the tool developed in this thesis is shown to i) speed up a trade-off analysis by domain-experts, and ii) also improve the access to biology information for nonexperts.