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Research on Improved K-Means Clustering Algorithm for Smart Energy Meter Based on Climatic Features Read chapter Read first chapter

2021 | OriginalPaper | Chapter

The Research on Disruptive Technology Identification Based on Scientific and Technological Information Mining and Expert Consultation: A Case Study on the Energy Field

Authors : Lucheng Lyu, Xuezhao Wang, Wei Chen, Xin Zhang, Xiaoli Chen, Xiwen Liu

Published in: Artificial Intelligence in China

Publisher: Springer Singapore

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Abstract

Disruptive technology identification is of great significance to the development of the countries and enterprises. In this paper, both quantitative analysis and qualitative analysis are combined to propose a disruptive technology identification method based on scientific and technological information mining and expert consultation. In the part of the quantitative analysis, three kinds of scientific and technological information data are involved including papers, patents, and projects, and the word embedding model and clustering technology are applied to dimension reduction and aggregation the scientific and technological information which results in finding “seeds” or “sprouts” of disruptive technologies from the mass scientific and technological information. In the part of the expert consultation, the ranking of potential disruptive technologies is evaluated by an expert questionnaire based on a “three-dimensional index system of technology disruptive potential evaluation.” The result of the energy field research is that 45 potential disruptive technologies are identified and their disruptive ranking is determined.

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Footnotes
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Metadata
Title
The Research on Disruptive Technology Identification Based on Scientific and Technological Information Mining and Expert Consultation: A Case Study on the Energy Field
Authors
Lucheng Lyu
Xuezhao Wang
Wei Chen
Xin Zhang
Xiaoli Chen
Xiwen Liu
Copyright Year
2021
Publisher
Springer Singapore
Book
Artificial Intelligence in China

Print ISBN: 978-981-15-8598-2

Electronic ISBN: 978-981-15-8599-9

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-8599-9_54

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