2021
DOI: 10.1007/978-3-030-73103-8_53
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A Systematic Literature Review about Idea Mining: The Use of Machine-Driven Analytics to Generate Ideas

Abstract: Idea generation is the core activity of innovation. Digital data sources, which are sources of innovation, such as patents, publications, social media, websites, etc., are increasingly growing at unprecedented volume. Manual idea generation is time-consuming and is affected by the subjectivity of the individuals involved. Therefore, the use machine-driven data analytics techniques to analyze data to generate ideas and support idea generation by serving users is useful. The objective of this study is to study s… Show more

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Cited by 5 publications
(2 citation statements)
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“…This challenge is exacerbated by the fact that many symptom terms identified through these methods may not necessarily be user-related content but could be news reports or general discussions about health events [25][26][27]. The accuracy of symptom identification and classification is paramount for ensuring the integrity of individual analysis, as misclassification of posts and inaccurate reporting on user-related health events can lower the confidence of subsequent data analysis [28].…”
Section: Introductionmentioning
confidence: 99%
“…This challenge is exacerbated by the fact that many symptom terms identified through these methods may not necessarily be user-related content but could be news reports or general discussions about health events [25][26][27]. The accuracy of symptom identification and classification is paramount for ensuring the integrity of individual analysis, as misclassification of posts and inaccurate reporting on user-related health events can lower the confidence of subsequent data analysis [28].…”
Section: Introductionmentioning
confidence: 99%
“…However, research on AI in design has a long history and a well-established community including journals such as AI EDAM 1 and conferences such as DCC 2 . Researchers have explored a variety of potential roles that AI systems can play in the design process (Ayele & Juell-Skielse, 2021;Gero & Kannengiesser, 2014;Karimi et al, 2019), but a key focus has been on computational creativity. That is, the ability of computational systems to support creative thinking and the development of ideas (Sosa & Gero, 2016).…”
Section: Introductionmentioning
confidence: 99%