Using association reasoning tool to achieve semantic reframing of service design insight discovery

Yuan, Soe‐Tsyr; Hsieh, Pei-Kang

doi:10.1016/j.destud.2015.07.001

Cited by 13 publications

(18 citation statements)

References 16 publications

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“…Triplets classification (Cheong et al, 2017) ConceptNet Knowledge retrieval and reasoning (Yuan and Hsieh, 2015) Concept association and expansion (Han et al, 2018a) Knowledge retrieval and reasoning (Han et al, 2018b) Query expansion; ideation aid (Chen and Krishnamurthy, 2020) Hand-built extracting thematic relations in domain-specific knowledge Knowledge retrieval and reasoning (Georgiev et al, 2017) Total technology space map (TSM) Knowledge retrieval and reasoning (Luo et al, 2018; B-Link Cross-domain knowledge associations (Chen et al, 2019) TechNet Prior art search, design knowledge discovery and representation, idea generation and evaluation (Sarica et al, 2019a;2019b;Han et al, 2020) SAPPhIRE model ontology Knowledge retrieval (Acharya and Chakrabarti, 2020)…”

Section: Semantic Network As Knowledge Bases For Engineering Designmentioning

confidence: 99%

Semantic Networks for Engineering Design: A Survey

2021

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There have been growing uses of semantic networks in the past decade, such as leveraging large-scale pre-trained graph knowledge databases for various natural language processing (NLP) tasks in engineering design research. Therefore, the paper provides a survey of the research that has employed semantic networks in the engineering design research community. The survey reveals that engineering design researchers have primarily relied on WordNet, ConceptNet, and other common-sense semantic network databases trained on non-engineering data sources to develop methods or tools for engineering design. Meanwhile, there are emerging efforts to mine large scale technical publication and patent databases to construct engineering-contextualized semantic network databases, e.g., B-Link and TechNet, to support NLP in engineering design. On this basis, we recommend future research directions for the construction and applications of engineering-related semantic networks in engineering design research and practice.

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Section: Semantic Network As Knowledge Bases For Engineering Designmentioning

confidence: 99%

Semantic Networks for Engineering Design: A Survey

2021

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“…The participants created a concept map to visualise what they were thinking and how they expanded their thoughts. Concept map is a technique that helps to generate, organise, and visualise the ideas, which was used in a software of supporting to gain insights in design [2]. In the third step, the participants were to write down at least one insight in eight minutes, based on their analysis of the transcript.…”

Section: Figure 2 An Excerpt Of the Given Interview Transcriptmentioning

confidence: 99%

“…In the third step, the participants were to write down at least one insight in eight minutes, based on their analysis of the transcript. A template of insight was given to the participants, which was "'OO' needs 'XX', because '…'", because good insights should have comprised, the user, their needs, and the reason why they needed it [2]. 'OO' was the subject of the phrase, 'XX' was what 'OO' needs, and the reason was written in '…'.…”

Section: Figure 2 An Excerpt Of the Given Interview Transcriptmentioning

confidence: 99%

“…To be successful in today's market, companies aim at developing innovative ideas of new products or services, which respond to the underlying user-needs [1]. To develop innovative solutions, it is crucial to find a clear and right problem to be solved by designs, which can be achieved by discovering insights from the target users [2,3]. Insight in design is defined as a "clear, deep, meaningful perception into a particular design contexts" [4].…”

Section: Introductionmentioning

confidence: 99%

“…Insight in design is defined as a "clear, deep, meaningful perception into a particular design contexts" [4]. Gaining insight is one of the most important challenges in design process [2]. It is critical to get deep empathy with the users to gain meaningful insights [1].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

How Should Designers Formulate Users Insight? - Comparison Between Novices and Professionals

Taoka¹,

Egashira²,

Saito³

2021

DS 110: Proceedings of the 23rd International Conference on Engineering and Product Design Education (EPDE 2021)

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This research investigated the difference between novice and professional designers in terms of skills of gaining insights into design process. This study experimentally examined the designers' behaviours in gaining insight by comparing how novice and professional designers empathise differently toward users. In the experiment, designers were asked to create a concept map and gain insights from a prepared userinterview transcript. The participants were interviewed about how they gained insights of users from the transcript. The concept map and insight statements were analysed. As a result, we clarified a difference between novice and professional designers which were generalisation of the transcript and inclusion of suppositions into insight statements. This study is a first step to analyse and support the insight generation of novice designers.

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Design representation as semantic networks

Han

Luo

2023

Computers in Industry

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Using association reasoning tool to achieve semantic reframing of service design insight discovery

Cited by 13 publications

References 16 publications

Semantic Networks for Engineering Design: A Survey

Semantic Networks for Engineering Design: A Survey

How Should Designers Formulate Users Insight? - Comparison Between Novices and Professionals

Design representation as semantic networks

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