重新审查专利引文

Jeffrey M. Kuhn, Kenneth Younge, Alan C. Marco
{"title":"重新审查专利引文","authors":"Jeffrey M. Kuhn, Kenneth Younge, Alan C. Marco","doi":"10.2139/ssrn.2714954","DOIUrl":null,"url":null,"abstract":"Existing measures of innovation often rely on patent citations to indicate intellectual lineage and impact. We show that the data generating process for patent citations has changed substantially since citation-based measures were validated a decade ago. Today, far more citations are created per patent, and the mean technological similarity between citing and cited patents has fallen significantly. These changes suggest that the use of patent citations for scholarship needs to be re-validated. We develop a novel vector space model to examine the information content of patent citations, and show that methods for sub-setting and/or weighting informative citations can substantially improve the predictive power of patent citation measures. We make data for a basic correction available for future scholarship through the Patent Research Foundation.","PeriodicalId":419336,"journal":{"name":"Management of Innovation eJournal","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"87","resultStr":"{\"title\":\"Patent Citations Reexamined\",\"authors\":\"Jeffrey M. Kuhn, Kenneth Younge, Alan C. Marco\",\"doi\":\"10.2139/ssrn.2714954\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Existing measures of innovation often rely on patent citations to indicate intellectual lineage and impact. We show that the data generating process for patent citations has changed substantially since citation-based measures were validated a decade ago. Today, far more citations are created per patent, and the mean technological similarity between citing and cited patents has fallen significantly. These changes suggest that the use of patent citations for scholarship needs to be re-validated. We develop a novel vector space model to examine the information content of patent citations, and show that methods for sub-setting and/or weighting informative citations can substantially improve the predictive power of patent citation measures. We make data for a basic correction available for future scholarship through the Patent Research Foundation.\",\"PeriodicalId\":419336,\"journal\":{\"name\":\"Management of Innovation eJournal\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"87\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Management of Innovation eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.2714954\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Management of Innovation eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2714954","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 87

摘要

现有的创新衡量标准往往依赖于专利引用来表明知识谱系和影响。我们表明,自十年前基于引文的测量方法得到验证以来,专利引文的数据生成过程发生了重大变化。如今,每项专利被引用的次数要多得多,被引用专利和被引用专利之间的平均技术相似性显著下降。这些变化表明,使用专利引用奖学金需要重新验证。我们开发了一个新的向量空间模型来检验专利引文的信息含量,并表明子集和/或加权信息引文的方法可以大大提高专利引文度量的预测能力。我们通过专利研究基金会为将来的奖学金提供基本校正数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Patent Citations Reexamined
Existing measures of innovation often rely on patent citations to indicate intellectual lineage and impact. We show that the data generating process for patent citations has changed substantially since citation-based measures were validated a decade ago. Today, far more citations are created per patent, and the mean technological similarity between citing and cited patents has fallen significantly. These changes suggest that the use of patent citations for scholarship needs to be re-validated. We develop a novel vector space model to examine the information content of patent citations, and show that methods for sub-setting and/or weighting informative citations can substantially improve the predictive power of patent citation measures. We make data for a basic correction available for future scholarship through the Patent Research Foundation.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信