Edinburgh Napier University

  This research sets out a new interpretation of the patent database using affective design parameters. While this resource contains a vast quantity of technical information, its extraction and use in practical design settings is extremely challenging. Until now, all filing and subsequent landscaping or profiling of patents has been based on their technical characteristics. We set out an alternative approach that utilises crowdsourcing to first summarise patents and then applies text analysis tools to assess the summarising text in relation to three affective parameters: appearance, ease of use, and semantics. The results been used to create novel patent clusters that provide an alternative perspective on relevant technical data, and support user-centric engineering design. The workflow and tasks to effectively interface with the crowd are outlined, and the process for harvesting and processing responses using a combination of manual and computational analysis is reviewed. The process creates sets of descriptive words for each patent which differ significantly from those created using only functional requirements, and support a new paradigm for the use of big data in engineering design – one that utilises desirable affective qualities as the basis for scouring and presenting relevant functional patent information for concept generation and development.