Advanced Methods: Identification of Promising High-Tech Solutions with Semantic Technologies: Energy, Pharma, and Other Industries

Irina Efimenko and Vladimir F. Khoroshevsky

Chapter 16 in Innovation Discovery:Network Analysis of Research and Invention Activity for Technology Management, 2018, pp 431-469 from World Scientific Publishing Co. Pte. Ltd.

Abstract: A novel approach to trend monitoring and the identification of promising high-tech solutions is presented in the chapter. It is based on the ontology of a technology/market trend, Hype Cycles methodology, and semantic indicators which provide evidence of a maturity level of a technology as well as of emerging user needs (customer pains) in high-tech industries. This approach forms the basis for text mining software tools implemented in Semantic Hub platform. The algorithms behind these tools allow users to escape from getting too general or garbage results which make it impossible to identify promising technologies at early stages (early detection, weak signals). Besides, these algorithms provide high-quality results in the extraction of complex multiword terms which correspond to technological concepts and user pains forming a trend. The methodology and software developed as a result of this study are applicable to various industries with minor adjustments.

Keywords: Bibliometrics; Technology Management; Patents; Innovation; Scientometric; Network Analysis; Network Tools (search for similar items in EconPapers)
JEL-codes: O32 (search for similar items in EconPapers)
Date: 2018
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