[Purpose/significance] This paper proposed a technology opportunity discovery method which integrated comment topic identification and multi-dimensional analysis of technology attributes, identified technology opportunities from the perspective of technology demand driven, and provided decision-making support for enterprises' forward-looking layout of R & D direction and scientific research management planning. [Method/process] Product online comments were used as the research data source. Firstly, LDA topic model was used to identify the technical topics of comments, and two indicators of technical comment topic strength and topic novelty were proposed to screen out the emerging key technical comment topics. Then, technical attribute words were manually selected from academic papers and technical patents, and high-frequency comment words were obtained through TF-IDF value calculation. Combined with expert knowledge, technical feature words were further selected, and product technical attribute words technical feature words list was constructed. Through the correlation calculation, the technical attributes related to the comments and the topics of the emerging key technology comments were obtained respectively. Finally, this paper proposed an index model to identify important technical attributes of products, and designed a multi-dimensional analysis method to analyze the characteristics of important technical attributes of products, and finally identified the emerging technology opportunities contained in the comment text. [Result/conclusion] The experimental results show that this method can effectively identify technology opportunities prospectively, and provide reference for enterprise product technology R & D management.
Wu Yiping
,
Bai Rujiang
,
Liu Mingyue
,
Wang Xiaoyue
. Research on Technology Opportunity Discovery Based on Comment Topic Identification and Multi Dimension Analysis of Technical Attributes[J]. Library and Information Service, 2021
, 65(10)
: 56
-67
.
DOI: 10.13266/j.issn.0252-3116.2021.10.007
[1] LI X, XIE Q,JIANG J J.Identifying and monitoring the development trends of emerging Technologies using patent analysis and Twitter data mining:the case of perovskite solar cell Technology[J]. Technological forecasting & social shange,2019,146:687-705.
[2] ZHU D H,PORTER A. Automated extraction and visualization of information for Technological intelligence and forecasting[J]. Technological forecasting & social shange,2002,69(5):495-506.
[3] PORTER A,MICHAEL J.DETAMPEL. Technology opportunities analysis[J]. Technological forecasting & social shange,1995. 49(3):237-255.
[4] 李保明.技术机会与技术创新的决策[J].科学管理研究,1990(5):61-62.
[5] 陈震红,董俊武.创业机会的识别过程研究[J].科技管理研究,2005(2):133-136.
[6] 康宇航,苏敬勤.技术创新机会的可视化识别——基于专利计量的实证分析[J].科学学研究,2008(4):695-701.
[7] CECERE G,REXHÄUSWE S,SCHULTE P.From less promising to green? technological opportunities and their role in (green) ICT Innovation[J].Economics of innovation and new technology, 2019,28(1), 45-63.
[8] ORSENIGO L, MALERBA F. Technological regimes and sectoral patterns of innovative activities[J]. Industrial and corporate change, 1997, 6(1):83-117.
[9] 李欣,谢前前,洪志生,等.基于社会感知分析的新兴技术发展趋势研究——以钙钛矿太阳能电池技术为例[J].科技进步与对策,2018,35(10):15-24.
[10] 何传启.新科技革命的预测和解析[J].科学通报,2017,62(8):785-798.
[11] 李欣,黄鲁成.技术路线图方法探索与实践应用研究——基于文献计量和专利分析视角[J].科技进步与对策,2016,33(5):62-72.
[12] CHO T S,SHIH H Y. Patent citation network analysis of core and emerging Technologies in Taiwan:1997-2008[J]. Scientometrics,2011,89(3):795-811.
[13] Lee S,Yoon B,Park Y. An approach to discovering new Technology opportunities:keyword-based patent map approach[J]. Technovation,2008,29(6):481-497.
[14] 翟东升,郭程,张杰,李登杰.采用异常检测的技术机会识别方法研究[J].现代图书情报技术,2016(10):81-90.
[15] 王京安,汤月,王坤.基于Citespace的技术机会发现研究——以物联网技术发展为例[J].现代情报,2018,38(2):130-137,170.
[16] WANG M Y,FANG S C,CHANG Y H. Exploring technological opportunities by mining the gaps between science and TECH-nology:microalgal biofuels[J].Technological forecasting & social shange,2015,92:182-195.
[17] SONG K, KIM K S,LEE S. Discovering new technology opportunities based on patents:text-mining and F-term analysis[J]. Technovation,2017(60/61):1-14.
[18] 韩晓彤,刘燕新,任智军,等.基于专利挖掘的技术竞争对手研发方向识别[J].科学学与科学技术管理,2018,39(2):23-32.
[19] BLEI D M, NG A Y, JORDAN M I. Latent dirichlet allocation[J]. The Journal of machine learning research, 2003(3):993-1022.
[20] 张振亚,王进,程红梅,等.基于余弦相似度的文本空间索引方法研究[J]. 计算机科学, 2005, 032(009):160-163.
[21] 荣耀9X充电续航实测,充电时间让人头疼但续航表现令人惊喜[EB/OL].[2020-11-14]. https://www.sohu.com/a/331268635_120156943.
