基于专利动态指标的新兴技术预测建模方法

doi:10.3772/j.issn.1000-0135.2022.08.002

情报学报

2022, Vol. 41

Issue (8): 786-795 DOI: 10.3772/j.issn.1000-0135.2022.08.002

情报理论与方法

本期目录 | 过刊浏览 | 高级检索

基于专利动态指标的新兴技术预测建模方法

杨冠灿¹, 丁月¹, 徐硕², 卢小宾¹

1.中国人民大学信息资源管理学院，北京 100872
2.北京工业大学经济管理学院，北京 100124

Formulation of a Predictive Modeling Approach for Emerging Technologies: Based on Patent Dynamic Indicators in the Cancer Drug Area

Yang Guancan¹, Ding Yue¹, Xu Shuo², Lu Xiaobin¹

1.School of Information Resource Management, Renmin University of China, Beijing 100872
2.College of Economic and Management, Beijing University of Technology, Beijing 100124

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摘要新兴技术是技术创新管理、科技政策制定和技术竞争情报研究领域关注的重点问题，随着大数据挖掘技术的兴起，针对海量专利数据的自动化新兴技术识别与预测，逐渐成为当前的研究热点。本研究的核心目的是识别未来哪些癌症药物专利最有可能成为新兴技术。本研究的主要贡献是：首先，是从前向视角（ex ante）进行预测而不是采用回溯视角；其次，针对癌症药物领域新兴技术预测面临的数据不均衡、早期预测需求提供了一套完整的分析框架。最终，通过研究证实了利用监督学习方法构建的包含动态专利指标的模型对新兴技术具有较好的预测效果，尤其是，动态指标“前向专利家族”和“前向引文”对增强模型的效果具有显著作用。

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	杨冠灿
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关键词 ：新兴技术, 逻辑回归, 不均衡数据, 癌症药物领域

收稿日期: 2021-06-09

基金资助:国家社会科学基金重点项目“新时期产业技术情报分析方法体系研究”（21ATQ008）。

作者简介: 杨冠灿，男，1981年生，博士，副教授，研究方向为专利数据挖掘、技术竞争情报；丁月，女，1996年生，硕士研究生，研究方向为专利数据挖掘、技术竞争情报；徐硕，男，1980年生，博士，教授，研究方向为技术预见、科学前沿探测、数据挖掘；卢小宾，男，1963年生，博士，教授，博士生导师，研究方向为信息分析，E-mail：luxb@ruc.edu.c；

引用本文:

杨冠灿, 丁月, 徐硕, 卢小宾. 基于专利动态指标的新兴技术预测建模方法[J]. 情报学报, 2022, 41(8): 786-795.
Yang Guancan, Ding Yue, Xu Shuo, Lu Xiaobin. Formulation of a Predictive Modeling Approach for Emerging Technologies: Based on Patent Dynamic Indicators in the Cancer Drug Area. 情报学报, 2022, 41(8): 786-795.

链接本文:

https://qbxb.istic.ac.cn/CN/10.3772/j.issn.1000-0135.2022.08.002 或 https://qbxb.istic.ac.cn/CN/Y2022/V41/I8/786

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