图书情报工作 ›› 2021, Vol. 65 ›› Issue (10): 56-67.DOI: 10.13266/j.issn.0252-3116.2021.10.007

• 情报研究 • 上一篇    下一篇

融合评论主题识别与技术属性多维度分析的技术机会发现研究

吴一平, 白如江, 刘明月, 王效岳   

  1. 山东理工大学信息管理研究院 淄博 255049
  • 收稿日期:2020-11-30 修回日期:2021-01-23 出版日期:2021-05-20 发布日期:2021-06-02
  • 通讯作者: 白如江(ORCID:0000-0003-3822-8484),研究馆员,硕士生导师,通讯作者,E-mail:brj@sdut.edu.cn
  • 作者简介:吴一平(ORCID:0000-0001-9426-7328),硕士研究生;刘明月(ORCID:0000-0002-4335-9369),硕士研究生;王效岳(ORCID:0000-0002-7100-7758)教授,博士,硕士生导师。
  • 基金资助:
    本文系山东省高等学校青创科技支持计划"科技大数据驱动的智慧决策支持创新团队-面向新旧动能转换的新兴科学研究前沿识别研究"(项目编号:2019RWG033)研究成果之一。

Research on Technology Opportunity Discovery Based on Comment Topic Identification and Multi Dimension Analysis of Technical Attributes

Wu Yiping, Bai Rujiang, Liu Mingyue, Wang Xiaoyue   

  1. Institute of Information Management, Shandong University of Technology, Zibo 255049
  • Received:2020-11-30 Revised:2021-01-23 Online:2021-05-20 Published:2021-06-02

摘要: [目的/意义] 提出一种融合评论主题识别与技术属性多维度分析的技术机会发现方法,从技术需求驱动视角识别技术机会,为企业前瞻布局研发方向与进行科研管理规划提供决策建议支持。[方法/过程] 以产品在线评论为研究数据源,首先,利用LDA主题模型识别出评论技术主题,提出技术评论主题强度和主题新颖度两个指标,筛选出新兴重点技术评论主题。然后,从学术论文、技术专利中人工选取技术属性词,通过TF-IDF值计算得到评论高频词,结合专家知识进一步筛选出技术特征词,构建产品技术属性词-技术特征词表。通过相关性计算分别得到与评论相关和与新兴重点技术评论主题相关的技术属性。最后,提出一种产品重要技术属性识别指标模型并设计一种多维度分析方法,分析产品重要技术属性的特征情况,最终识别出蕴含在评论文本中的新兴技术机会。[结果/结论] 实验结果表明该方法能够有效地识别技术机会,为企业产品技术研发管理提供参考。

关键词: 技术机会发现, 技术属性分析, 主题识别, 评论挖掘

Abstract: [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.

Key words: technology opportunities discovery, technical attributes analysis, subject recognition, comments mining

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