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现代图书情报技术  2016, Vol. 32 Issue (7-8): 60-69     https://doi.org/10.11925/infotech.1003-3513.2016.07.08
  本期目录 | 过刊浏览 | 高级检索 |
新兴技术发现模型研究*
任智军1,2(),乔晓东1,张江涛2
1中国科学技术信息研究所 北京 100038
2国家知识产权局中国专利信息中心 北京 100088
Discover Emerging Technologies with LDA Model
Ren Zhijun1,2(),Qiao Xiaodong1,Zhang Jiangtao2
1Institute of Scientific & Technical Information of China, Beijing 100038, China
2The China Patent Information Center, The State Intellectual Property Office, Beijing 100088, China
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摘要 

目的】在论文和专利中识别并发现待选新兴技术。【方法】采用LDA模型寻找技术主题, 使用新兴技术相似度识别待选新兴技术。利用电动汽车数据进行实验分析。【结果】实验结果表明, 该方法区别于以往的新兴技术识别方法, 自动识别出电动汽车领域的25个新兴技术。【局限】没有进行专家打分实验, 模型分析结果未与人工结果进行对比。【结论】新兴技术发现模型可高效发现新兴技术, 有效减少专家阅读文献的数量。

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任智军
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关键词 新兴技术论文专利电动汽车技术相似度    
Abstract

[Objective] To identify emerging technologies from academic papers and patents. [Methods] We adopted the Latent Dirichlet Allocation (LDA) model to find technical topics and used the similarity theory to retrieve emerging technologies from the electric car data. [Results] The proposed method was more efficient than exisiting ones. It reduced the subjectivity of the experts’ evaluation and the amount of data to be analyzed. [Limitations] We did not include the expert scoring experiment in this study, thus, we could not compare the new model’s performance with those involving human judgements. [Conclusions] The proposed model could identify emerging technologies effectively and then reduce the document reading load of the experts.

Key wordsEmerging technology    Paper    Patent    Electric car    Technology similarity
收稿日期: 2016-01-22      出版日期: 2016-09-29
基金资助:*本文系中国博士后科学基金资助项目“基于论文与专利整合的分析与挖掘方法研究”(项目编号: 2013M540125)的研究成果之一
引用本文:   
任智军,乔晓东,张江涛. 新兴技术发现模型研究*[J]. 现代图书情报技术, 2016, 32(7-8): 60-69.
Ren Zhijun,Qiao Xiaodong,Zhang Jiangtao. Discover Emerging Technologies with LDA Model. New Technology of Library and Information Service, 2016, 32(7-8): 60-69.
链接本文:  
https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2016.07.08      或      https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2016/V32/I7-8/60
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