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| Exploring Potential Collaboration Partners of Middle and Small-sized Enterprises Based on Heterogeneous Information Networks of Patent: Graphene as Example |
| Fu Junying1, Peng Zhe2, Zheng Jia1, Yuan Fang1, Li Nong1 |
1.Institute of Scientific and Technical Information of China, Beijing 100038
2.Business-Intelligence of Oriental Nations Corporation Ltd., Beijing 100102 |
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Abstract The technological innovation capability of small- and medium-sized enterprises (SMEs) has become an important component of a country’s national innovation system. In the US, there have been very comprehensive support measures related to SMEs that encourage them to cooperate with external organizations, such as non-profit research institutions and large enterprises; the support, in turn, can help them to develop rapidly. This study seeks to measure the technical similarity of the patentees by measuring the similarity between their patents and builds a heterogeneous network based on graphene-related patents in the database on US-authorized patents. Further, based on the PathSelClus algorithm, we choose 7 scientific research institutions and 5 large enterprises to act as user guidance. As a result, we get 2 types of clusters in terms of 2 semantics. The first result is a distribution of the degree of similarity between the SMEs and the 7 scientific research institutions, and the other is a distribution of the degree of similarity between SMEs and the 5 large enterprises. Finally, this study analyzes the validity of clustering results according to the research and development direction of the patentees.
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Received: 24 October 2018
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1 何光辉. 发达国家扶持中小企业技术创新政策及启示[J]. 软科学, 2012, 26(6): 119-120, 144.
2 张小冲, 张学军. 经济体制改革前沿问题: 国际比较与借鉴[M]. 北京: 人民出版社, 2003.
3 赵亚静. 我国中小企业知识产权建设政策体系研究[D]. 长春: 东北师范大学, 2012: 5-7.
4 杨西春. 中小企业技术创新与政策环境优化[J]. 人民论坛, 2014(1): 87-89.
5 李英. 提升浙江省中小企业国际竞争力的对策研究[D]. 杭州: 浙江工业大学, 2008: 6-10.
6 李敏. 试析自主创新对他国经济发展的影响与作用[N/OL]. 中国信息报, (2007-08-22) [2016-6-23]. http: //www. zgxxb. com. cn/jsdk/201002244255. shtm.
7 洪勇, 李英敏. 基于专利耦合的企业间技术相似性可视化研究[J]. 科学学研究, 2013, 31(7): 1013-1021.
8 徐元浩. 基于潜在语义分析的专利文献分析与搜索技术的研究[D]. 杭州: 浙江大学, 2010: 7-8.
9 KesslerM M. Bibliographic coupling between scientific papers[J]. American Documentation, 1963, 35(3): 401-420.
10 HuangM H, ChiangM H, LiY, et al. Constructing a patent citation map using bibliographic coupling: A study of Taiwan’s high-tech companies[J]. Scientometrics, 2003, 58(3): 489-505.
11 吕惠琳, 刘杨. 基于专利耦合的波导光互联企业技术相似性分析[J]. 情报探索, 2016(1): 8-11.
12 SmallH. Cocitation in the scientific literature: a new measure of the relationship between two documents[J]. Journal of American Society for Information Science, 1973, 24(4): 265-269.
13 WhiteH D, GriffieldB C. Author cocitation: A literature measure of intellectual structure[J]. Journal of the American Society for Information Science, 1981, 32(3): 163-171.
14 MagermanT, Van LooyB, SongX Y. Exploring the feasibility and accuracy of Latent Semantic Analysis based text mining techniques to detect similarity between patent documents and scientific publications[J]. Scientometrics, 2010, 82(2): 289-306.
15 陈芨熙, 顾新建, 陈国海. 基于向量空间模型和专利文献特征的相似专利确定方法[J]. 浙江大学学报(工学版), 2009, 43(10): 1848-1852.
16 YoonB, ParkY. A text-mining-based patent network: Analytical tool for high-technology trend[J]. The Journal of High Technology Management Research, 2004, 15(1): 37-50.
17 季铎, 毕臣, 蔡东风. 基于类别信息优化的潜在语义分析分类技术[J]. 中国科学技术大学学报, 2015, 45(4): 314-320.
18 JanssensF. Clustering of science fields by integrating text mining and bibliometrics[D]. Belgium: Katholieke University Leuven, 2007.
19 LiuX H, YuS, FrizoJ, et al. Weighted hybrid clustering by combing text mining and bibliometrics on a large-scale journal database[J]. Journal of the American Society for Information Science and Technology, 2010, 61(6): 1105-1119.
20 任红娟. 基于文献内容和引用结合的知识结构分析方法研究[D]. 北京: 中国科学院研究生院, 2010.
21 WangF, DingC, LiT. Integrated KL (K-means-Laplacian) clustering: A new clustering approach by combining attribute data and pairwise relations[C]// Proceedings of the 2009 SIAM International Conference on Data Mining. DBLP, 2009: 38-48.
22 温芳芳. 专利分类号耦合分析在企业潜在合作关系识别中的应用[J]. 现代情报, 2018(7): 142-147.
23 温芳芳. 基于专利权人-分类号多重共现分析的全球专利布局研究——以太阳能汽车技术领域为例[J]. 现代情报, 2017(4): 165-169.
24 李立. 基于元路径选择和融合的异构信息网络社区挖掘算法研究[D]. 西安: 西安电子科技大学, 2014: 8-17.
25 SunY, HanJ. Meta-path-based search and mining in heterogeneous information networks[J]. Tsinghua Science and Technology, 2013, 18(4): 329-338.
26 SunY Z, NorickB, HanJ W, et al. PathSelClus: Integrating meta-path selection with user-guided object clustering in heterogeneous information networks[J]. ACM Transactions on Knowledge Discovery from Data, 2013, 7(3): Article No. 11.
27 SunY Z, HanJ W, YanX F, et al. Pathsim: Meta path-based top-k similarity search in heterogeneous information networks[J]. Proceedings of the VLDB Endowment, 2011, 4(11): 992-1003.
28 葛军. 异构信息网络上的相似性搜索研究[D]. 西安: 西安电子科技大学, 2013: 5-9.
29 步少莉. 异构信息网络Top-k相关性查询方法研究[D]. 山东: 山东大学, 2014: 5-8.
30 梅进, 张笑. 2010年诺贝尔物理学奖揭晓[EB/OL]. (2010-10-5) [2016-06-20]. http://news.sciencenet.cn/htmlnews/2010/10/238322.shtm.
31 李明珍. 石墨烯领域发展态势及对策建议[J]. 科技与经济, 2014, 27(1): 101-105.
32 叶春涛. 国外中小企业技术创新的现状及启示[J]. 经济研究导刊, 2013(22): 259-260. |
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