摘要
【目的】从识别指标信息的多元与不同赋权及排序算法组配的综合视角,结合大规模数据集的特点,研究核心专利组合识别方法的构建及其应用对比。【方法】通过交叉组配构建5种组合识别方法,选取6项专利特征信息,以人工智能领域为例,从整体与局部层次对比各方法的特征和应用情境。【结果】不同组合识别方法在不同的数据集与时间段有较高的一致性。同时,不同方法识别的结果随着被识别的核心专利数量增加而两两间重合率逐渐减少,例如方法(1)与方法(4)的核心专利重合率由80%降至47%。【局限】仅考虑现实研究中较普遍的核心识别需求,可进一步研究针对特定的、个性化的核心识别需求的专利组合识别方法。【结论】所构建的5种组合识别方法,基于专利数据集的规模、分散程度、时间跨度和特征值表现及技术领域发展的差异,可分别应用到核心专利识别不同应用需求场景中。针对快速发展的人工智能领域,熵权法赋权结合灰色关联分析和熵权法赋权结合TOPSIS这两种方法识别效果更优。
[Objective]This paper constructs identification methods for core patent portfolio and then examines their application with the help of large-scale datasets.[Methods]Through cross-combination,we constructed five identification models for the patents,which included six features of the patents.We then compared our methods’performance with datasets of artificial intelligence.[Results]Different combined methods yielded highly consistent results when applied to various datasets.Meanwhile,as the number of core patents increased,the duplicated rates between the two methods gradually decreased.For example,the core patent duplication rates of method(1)and method(4)dropped from 80%to 47%.[Limitations]We only investigated the common identification requirements.More research is needed to study those for specific and individualized areas.[Conclusions]The five constructed methods can be applied to different scenarios.For the rapidly developing field of artificial intelligence,the entropy weight method combining grey relational analysis and the entropy weight method with TOPSIS may yield better results.
作者
曾闻
王曰芬
Zeng Wen;Wang Yuefen(School of Intellectual Property,Nanjing University of Science and Technology,Nanjing 210094,China;School of Management,Tianjin Normal University,Tianjin 300380,China;Institute for Big Data Science,Tianjin Normal University,Tianjin 300380,China)
出处
《数据分析与知识发现》
CSSCI
CSCD
北大核心
2022年第11期61-71,共11页
Data Analysis and Knowledge Discovery
基金
国家社会科学基金重大项目(项目编号:16ZDA224)的研究成果之一。
关键词
核心专利识别
组合识别方法
单一赋权
组合赋权
Core Patent Identification
Combination Identification Methods
Single Weighting
Combination Weighting
