期刊文献+

专利发明人员兴趣转移模式研究

Discovering Interest Transition Patterns of Technological Inventors
下载PDF
导出
摘要 研究方向的选择与转变是专利发明人员在发明创造生涯中都要面对的重要问题。然而,目前针对发明人员群体兴趣转移模式的实证研究却并不多见。本文基于1976~2015美国专利商标局(USPTO)约591万个专利数据,获得了技术领域研究人员的专利所属类别信息,并度量了这些发明人员的兴趣转移轨迹。分析结果显示,专利发明人兴趣转移模式表现为:高产出的专利发明人员兴趣转移的跨度小,但停留在本领域的人数占比低;而低产出的发明人兴趣转移的范围更广,停留在原来研究领域的人数占比反而高。本文研究结果有助于加深对从事科技领域发明人群体行为模式的了解,也对制定相关科技政策,完善科技管理有参考和借鉴意义。 Though it is a pivotal issue for inventors to determine and change the technological direction in their inventive life, few studies have investigated the transition patterns of interest. This paper obtained the patent classification information based on patent datasets, including 5,915,849 patents provided by USPTO from 1976 to 2015. Then, this study measured the trajectory of interest in these inventions. It is interesting that few of productive inventors hold the original invention field. However, their transition distance of interest is far from broad. By contrast, unproductive inventors showed opposite characteristics. This study is helpful for our understanding of group behaviors of inventors, which concerned policymaking and technological innovation management.
作者 刘非凡 夏昊翔 LIU FeiFan XIA HaoXiang(Institute of Systems Engineering, Dalian University of Technology, Dalian 116024, China)
出处 《情报工程》 2017年第2期33-40,共8页 Technology Intelligence Engineering
基金 国家自然科学基金面上项目(71371040) 重点项目(71533001) 国家创新群体项目(71421001)的资助
关键词 兴趣转移 专利 科技管理 Interest transition, patent, science& technology management
  • 相关文献

参考文献2

二级参考文献30

  • 1黄昌宁,赵海.中文分词十年回顾[J].中文信息学报,2007,21(3):8-19. 被引量:246
  • 2Price D S. Little science,big science. New York:Columbia University Press, 1963.
  • 3Blei D, Ng A, Jordan M. Latent Dirichlet Allocation [ J]. Journal of Machine Learning Re-search, 2003, 3 :993-1022.
  • 4Rosen-Zvi M, Griffiths T, Steyvers M,et al. The author- topic model for authors and documents [ C ]//Proceedings of the 20th conference on uncertainty in artificial intelligence (UAI), Arlington: AUAI Press 2004: 487-494.
  • 5Steyvers M, Smyth P, Rosen-Zvi M, et al. Probabilistic author-topic models for information discovery [ C ]// Proceedings of the 10's ACM SIGKDD international conference on Knowledge discovery and data mining, New York: ACM Press, 2004: 306-315.
  • 6Mimno D, McCallum A. Expertise modeling for matching papers with reviewers[ C ]/! Proceedings of the 13'h ACM SIGKDD international conference on Knowledge discovery and data mining, New York :ACM Press,2007 : 500-509.
  • 7Kawamae N. Author interest topic model[ C l// Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval, New York: ACM Press, 2010: 887-888.
  • 8Kawamae N. Latent interest-topic model:finding the causal relationships behind dyadic data[ C ]//Proceedings of the 19th ACM CIKM international conference on Information and knowledge management, New York: ACM Press, 2010 : 649-658.
  • 9Wang X, Mohanty N, McCallum A. Group and topic discovery from relations and text[ C]//Proceedings of the 11 ,h ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York: ACM Press, 2005 : 28-35.
  • 10Song X, Lin C,Tseng B L,et al. Modeling and predicting personal information dissemination behavior [ C ]// Proceedings of the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York: ACM Press, 2005 : 479-488.

共引文献24

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部