Computer-aided mind map generation via crowdsourcing and machine learning

Abstract

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Natural language processing in-and-for design research

“…The develop phase capitalises on the concretised needs, problem statements and function structures from the define phase to generate solutions using various approaches such as mind-map, 6-3-5 sketching and design-by-analogy. Supports have been developed regarding the mind maps to generate nodes (Chen and Krishnamurthy 2020) and organise these into categories (Camburn et al 2020a). In the absence of user needs, scholars have proposed various approaches to initiate design opportunities from technology maps (Trappey et al 2014; Luo, Yan, and Wood 2017) and biomimicry strategies (Vandevenne et al 2016; Cao et al 2021).…”

“…Liu et al (2020, p. 6) summarise 1757 scientific articles (solutions to a transmission problem) by building Word2Vec-based semantic networks around the central keywords – {transmission, line, location, measurement, sensor and wave}. Camburn et al (2020a, 2020b) utilise HDBSCAN 23 for clustering crowdsourced concepts and TextRazor 24 for extracting entities and topics from these.…”

Design Knowledge Representation With Technology Semantic Network

“…Network metrics have provided a medium to derive useful design-related insights from the structure of the graphs, and various layout methods have provided ways of representing the design-related data in an easily comprehensible way (Lim et al, 2016;. For example, network visualizations have been utilized to represent the whole technology space to support innovation and competitive intelligence (Luo et al, 2017(Luo et al, , 2018Sarica, Yan, et al, 2020), show the relations between components and subsystems to evalute designs (He and Luo, 2017;Pasqual and De Weck, 2012;Sosa et al, 2007) and inform design decisions (Kim and Kim, 2012;Sosa et al, 2007), discover the patterns of design activities (Alstott et al, 2017;Cash et al, 2014;Cash and Štorga, 2015), reveal the structure of design document repositories to guide retrievals (Fu et al, 2013;Luo et al, 2021), and represent mind maps (Camburn, Arlitt, et al, 2020;Camburn, He, et al, 2020) and concept networks (Chen et al, 2019;Chen and Krishnamurthy, 2020;Liu et al, 2020;Sarica et al, 2019Sarica et al, , 2021Shi et al, 2017;Song, Evans, et al, 2020;Souili et al, 2015) for design ideation uses. On the other hand, a few studies explored other visualization methods such as word-clouds (He, Camburn, Liu, et al, 2019; based on design description texts.…”

Guiding data-driven design ideation by knowledge distance

“…Novel and feasible answers to these questions may lead to innovation. To seek answers to such innovation questions, structured ideation methods, such as brainstorming, mind mapping TRIZ and design heuristics [1][2][3][4] may facilitate creative thinking, although design ideation is also conditioned on the knowledge and experience of the designers. Design thinking, user studies and market research may reveal user needs as design opportunities [5][6][7], but such processes are often slow and resource consuming.…”