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基于决策树方法的专利被引影响因素研究
吕璐成1; 刘娅2; 杨冠灿2
2015
Source Publication情报理论与实践
Volume38Issue:2Pages:28-32
Abstract专利引用对于专利质量评价具有重要作用。本研究基于决策树方法对可能影响专利被引的12个影响因素与专利是否被引的潜在关系进行分析。研究最终发现,专利的最早优先权年是其中影响最为显著的因素,而后依次是权利要求数量、专利权人数量、是否转让、平均引用时滞、优先权国家,而其它6个指标的影响效果并不明显。
Other AbstractPatent citation analysis is important in patent quality evaluation. This paper proposed a method based on decision tree model to discover the hidden correspondence between citations and 12 influence factors. Result indicated that the year of priority was the most significant factor, followed by patent claims, patentees, assignment of patent, mean citations lag and priority country, and the rest of factors were less influential.
Keyword决策树 专利引用 数据挖掘
Subject Area情报技术
DOI10.16353/j.cnki.1000-7490.2015.02.006
Citation statistics
Document Type期刊论文
Identifierhttp://ir.las.ac.cn/handle/12502/8234
Collection中国科学院文献情报中心(北京)_情报研究部
Corresponding Author吕璐成
Affiliation1.中国科学院文献情报中心
2.中国科学技术信息研究所
First Author Affilication中国科学院文献情报中心
Corresponding Author Affilication中国科学院文献情报中心
Recommended Citation
GB/T 7714
吕璐成,刘娅,杨冠灿. 基于决策树方法的专利被引影响因素研究[J]. 情报理论与实践,2015,38(2):28-32.
APA 吕璐成,刘娅,&杨冠灿.(2015).基于决策树方法的专利被引影响因素研究.情报理论与实践,38(2),28-32.
MLA 吕璐成,et al."基于决策树方法的专利被引影响因素研究".情报理论与实践 38.2(2015):28-32.
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