基于多源数据的企业研发方向识别与评估
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摘要
[目的/意义]结合网络、专利及文献多源数据信息,建立企业研发方向识别与评估的研究框架。[方法/过程]通过网络爬虫爬取网络信息,并进行文本挖掘获取研发需求信息作为研究基础,结合企业领域专利需求信息二次检索,利用LDA主题模型及主成分分析法识别企业技术空白,确定企业研发方向,并采用技术价值与技术范围指标评估企业研发方向。最后以无人机领域A企业为例进行实证分析,通过文献信息佐证了研究的有效性。[结果/结论]综合基础研究与应用研究的多源数据信息有助于企业全面而综合识别并评估企业的研发方向,助力企业科学决策,为有效识别研发合作伙伴奠定基础。
[Purpose/Significance]The purpose of this research is to establish a research framework for identifying and evaluating R&D direction of enterprises from multiple sources by combing network,patent,and literature data.[Method/Process]The paper collected network information through web crawlers and adopted text mining to obtain R&D demand information and used it as a research basis. Combined with secondary search of enterprise domain patent demand information,using LDA topic model and principal component analysis method to identify enterprise technology gaps,the R&D direction for the enterprise was determined. The technical value and technical scope indicators were adopted to assess the R&D direction. Finally,enterprise A in the field of Unmanned Aerial Vehicle was introduced as an example for further analysis,and the validity of the research was supported by literature information.[Result/Conclusion]The multi-source data information based on comprehensive basic research and applied research could help enterprise identify and evaluate its R&D direction comprehensively,facilitate it to make scientific decisions,and lay a foundation for effectively identifying R&D partners.
[Purpose/Significance]The purpose of this research is to establish a research framework for identifying and evaluating R&D direction of enterprises from multiple sources by combing network,patent,and literature data.[Method/Process]The paper collected network information through web crawlers and adopted text mining to obtain R&D demand information and used it as a research basis. Combined with secondary search of enterprise domain patent demand information,using LDA topic model and principal component analysis method to identify enterprise technology gaps,the R&D direction for the enterprise was determined. The technical value and technical scope indicators were adopted to assess the R&D direction. Finally,enterprise A in the field of Unmanned Aerial Vehicle was introduced as an example for further analysis,and the validity of the research was supported by literature information.[Result/Conclusion]The multi-source data information based on comprehensive basic research and applied research could help enterprise identify and evaluate its R&D direction comprehensively,facilitate it to make scientific decisions,and lay a foundation for effectively identifying R&D partners.
引文
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[23]黄鲁成,吴菲菲,李欣.未来导向技术分析现状与思考[J].中国软科学,2010(12):50-58.
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[25]龚惠群,刘琼泽,黄超.机器人产业技术机会发现研究---基于专利文本挖掘[J].科技进步与对策,2014,31(5):70-74.
[26]徐明,姜南.我国专利密集型产业及其影响因素的实证研究[J].科学学研究,2013,31(2):201-208.
[27]武松,潘发明.SPSS统计分析大全[M].北京;清华大学出版社,2014.
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[29]张健东,刘强,曹德斌.无人机技术中国专利分布情况及其专利情报运用[J].国防科技,2013,34(5):75-80.
[30]Park Y,Lee S,Lee S.Patent analysis for promoting technology transfer in multi-technology industries:The Korean aerospace industry case[J].Journal of Technology Transfer,2012,37(3):355-374.
[31]Finn R L,Wright D.Unmanned aircraft systems:Surveillance,ethics and privacy in civil applications[J].Computer Law&Security Report,2012,28(2):184-194.
[32]贺明飞,李卫国,陈晨,等.2 kg以内起飞质量的无人机超长续航策略[J].兵工自动化,2018(3).
[33]彭一轩.无人机续航问题的分析与探究[J].电脑迷,2018(2).
[2]Hung K P,Chiang Y H.Open innovation proclivity,entrepreneurial orientation,andperceived firm performance[J]International Journal of Technology Management,2010,52(4):257-274.
[3]Hagedoorn,John.Inter-firm R&D partenships:An overviewof major trends and patterns since 1960[J].Research Policy,2001,31(4):477-492.
[4]郑彦宁,许晓阳,刘志辉.基于关键词共现的研究前沿识别方法研究[J].图书情报工作,2016,60(4):85-92.
[5]吴菲菲,杨梓,黄鲁成.基于创新性和学科交叉性的研究前沿探测模型---以智能材料领域研究前沿探测为例[J].科学学研究,2015,33(1):11-20.
[6]Fujita K,Kajikawa Y,Mori J,et al.Detecting research fronts using different types of weighted citation networks[C]//Technology Management for Emerging Technologies.IEEE,2012:267-275.
[7]Song K,Kim K S,Lee S.Discovering newtechnology opportunities based on patents:Text-mining and F-term analysis[J].Technovation,2017,60-61.
[8]Yoon B,Park Y.A systematic approach for identifying technology opportunities:Keyword-based morphology analysis[J].Technological Forecasting&Social Change,2005,72(2):145-160.
[9]吕一博,康宇航,王淑娟.基于共现分析的技术机会发现与可视化识别[J].科研管理,2012,33(4):80-85.
[10]马婷婷,汪雪锋,朱东华,等.基于专利的技术机会分析方法研究[J].科学学研究,2014,32(3).
[11]王效岳,刘自强,白如江,等.基于基金项目数据的研究前沿主题探测方法[J].图书情报工作,2017,61(13):87-98.
[12]Keeeun Lee,Inchae Park,Byungun Yoon.An approach for R&Dpartner selection in alliancesbetween large companies,and small and medium enterprises(SMEs):Application of bayesian networkand patent analysis[J].Sustainability,2016,8(2):117.
[13]廖晓,李志宏,席运江.基于加权知识网络分析的企业社区创新用户专家知识发现方法[J].系统工程理论与实践,2016,36(5):1268-1279.
[14]郭雯,刘爱.基于嵌入性视角的用户驱动创新模式研究---以互联网视听行业为例[J].科学学与科学技术管理,2016,37(2):88-98.
[15]Shluzas L MA,Leifer L J.The insight-value-perception(i VP)model for user-centered design[J].Technovation,2014,34(11):649-662.
[16]Romero D,Rabelo R J,Molina A.On the management of virtual enterprise's inheritance between virtual manufacturing&service enterprises:Supporting dynamic product-service business ecosystems[C]//International Ice Conference on Engineering,Technology and Innovation,2012:1-11.
[17]余菲菲,燕蕾.创新社区中用户创新的创新效应及意见探究:以海尔HOPE创新平台为例[J].科学学与科学技术管理,2017,38(2):55-67.
[18]张璐,吴菲菲,黄鲁成.基于用户网络评论信息的产品创新研究[J].软科学,2015,29(5):12-16.
[19]Cavdar A B,Ferhatosmanoˇglu N.Airline customer lifetime value estimation using data analytics supported by social network information[J].Journal of Air Transport Management,2018,19-33.
[20]Kwon H,Kim J,Park Y.Applying LSA text mining technique in envisioning social impacts of emerging technologies:The case of drone technology[J].Technovation,2017,60-61.
[21]许晓阳,郑彦宁,刘志辉.论文和专利相结合的研究前沿识别方法研究[J].图书情报工作,2016,60(24):97-106.
[22]黄鲁成,王静静,李欣,等.基于论文和专利的钙钛矿太阳能电池的技术机会分析[J].情报学报,2016,35(7):686-695.
[23]黄鲁成,吴菲菲,李欣.未来导向技术分析现状与思考[J].中国软科学,2010(12):50-58.
[24]黄鲁成,蔡爽.基于专利的判断技术机会的方法及实证研究[J].科学学研究,2010,28(2):215-220.
[25]龚惠群,刘琼泽,黄超.机器人产业技术机会发现研究---基于专利文本挖掘[J].科技进步与对策,2014,31(5):70-74.
[26]徐明,姜南.我国专利密集型产业及其影响因素的实证研究[J].科学学研究,2013,31(2):201-208.
[27]武松,潘发明.SPSS统计分析大全[M].北京;清华大学出版社,2014.
[28]Blei D M,Ng A Y,Jordan MI.Latent dirichletallocation[J].Journal of Machine Learning Research,2008(3):993-1022.
[29]张健东,刘强,曹德斌.无人机技术中国专利分布情况及其专利情报运用[J].国防科技,2013,34(5):75-80.
[30]Park Y,Lee S,Lee S.Patent analysis for promoting technology transfer in multi-technology industries:The Korean aerospace industry case[J].Journal of Technology Transfer,2012,37(3):355-374.
[31]Finn R L,Wright D.Unmanned aircraft systems:Surveillance,ethics and privacy in civil applications[J].Computer Law&Security Report,2012,28(2):184-194.
[32]贺明飞,李卫国,陈晨,等.2 kg以内起飞质量的无人机超长续航策略[J].兵工自动化,2018(3).
[33]彭一轩.无人机续航问题的分析与探究[J].电脑迷,2018(2).