Discovering the potential opportunities of scientific advancement and technological innovation: A case study of smart health monitoring technology

Yung-Chi Shen, Ming-Yeu Wang and Ya-Chu Yang

Technological Forecasting and Social Change, 2020, vol. 160, issue C

Abstract: Detecting potential opportunities for scientific advancement and technological progress is vital for academia and technology-based firms. While patent data have become an extensively employed source for technological forecasting, scientific publications that represent advanced knowledge provide a potential for technological commercialization. Thus, the primary purpose of this study intends to discover potential opportunities for scientific advancement and technological innovation by comparing the information in scientific publications and patents. Accordingly, this study applies text mining and the arbitrarily ORiented projected CLUSter generation (ORCLUS) algorithm to cluster important scientific and technological topics. To identify potential opportunities for scientific advancement or technological commercialization, the cosine similarity of tf-idf vectors is used to detect the semantic similarity between clustered scientific fields and technological fields. Smart health monitoring technology is the case employed in this study. The results not only demonstrate the effectiveness of the text-based clustering approach and semantic similarity for exploring technological opportunities but also identify the potential patenting opportunities in the management of smart health monitoring and the potential scientific advancement in home health care systems.

Keywords: Text mining; ORCLUS; Cosine similarity of tf-idf vectors; Smart health monitoring (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:160:y:2020:i:c:s0040162520310519

DOI: 10.1016/j.techfore.2020.120225

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