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2020 | OriginalPaper | Chapter

Clustering Analysis and Visualization of TCM Patents Based on Deep Learning

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Abstract

In the process of medicine innovation, pharmaceutical enterprises tend to seize the intellectual property highland actively. They engage in research and development independently, apply for patents for core technologies, or take the initiative to acquire patents from others. Before applying for patents by their own efforts or purchasing patents from others, pharmaceutical companies need to search for related patents in the patent pool and make a comparative analysis of them, in order to find technology blank areas as R&D objectives, or find valuable patents as potential acquisition targets. In this paper, we use deep learning technology and propose a semantic-based clustering algorithm for Traditional Chinese Medicine (TCM) patents, discarding the traditional literal–based text clustering method. We also give a visualization method for TCM patents, so as to facilitate pharmaceutical enterprises to intuitively understand the relevant patents.

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Literature
3.
go back to reference Higuchi, S., Fukui, M., Fujii, A., et al.: PRIME: a system for multi-lingual patent retrieval. In: Proceedings of Mt Summit VIII (2002) Higuchi, S., Fukui, M., Fujii, A., et al.: PRIME: a system for multi-lingual patent retrieval. In: Proceedings of Mt Summit VIII (2002)
4.
go back to reference Jones, G.: Toward higher effectiveness for recall-oriented information retrieval: a patent retrieval case study. Machine Translating (2012) Jones, G.: Toward higher effectiveness for recall-oriented information retrieval: a patent retrieval case study. Machine Translating (2012)
5.
go back to reference Chen, J.X., Gu, X.J., Chen, G.H., et al.: Ontology-based patent retrieval technologies. J. Zhejiang Univ. 43(12), 2213–2217+2224 (2009) Chen, J.X., Gu, X.J., Chen, G.H., et al.: Ontology-based patent retrieval technologies. J. Zhejiang Univ. 43(12), 2213–2217+2224 (2009)
6.
go back to reference Fujii, A.: Enhancing patent retrieval by citation analysis. In: International ACM SIGIR Conference on Research & Development in Information Retrieval. ACM (2007) Fujii, A.: Enhancing patent retrieval by citation analysis. In: International ACM SIGIR Conference on Research & Development in Information Retrieval. ACM (2007)
7.
go back to reference Lei, L., Qi, J., Zheng, K.: Patent analytics based on feature vector space model: a case of IoT. IEEE Access 7, 45705–45715 (2019)CrossRef Lei, L., Qi, J., Zheng, K.: Patent analytics based on feature vector space model: a case of IoT. IEEE Access 7, 45705–45715 (2019)CrossRef
8.
go back to reference Narin, F., Carpenter, M.P., Woolf, P.: Technological performance assessments based on patents and patent citations. IEEE Trans. Eng. Manag. 31(4), 172–183 (2017)CrossRef Narin, F., Carpenter, M.P., Woolf, P.: Technological performance assessments based on patents and patent citations. IEEE Trans. Eng. Manag. 31(4), 172–183 (2017)CrossRef
9.
go back to reference Liu, D.R., Shih, M.J.: Hybrid-patent classification based on patent-network analysis. J. Am. Soc. Inform. Sci. Technol. 62(2), 246–256 (2011)CrossRef Liu, D.R., Shih, M.J.: Hybrid-patent classification based on patent-network analysis. J. Am. Soc. Inform. Sci. Technol. 62(2), 246–256 (2011)CrossRef
10.
go back to reference Chu, X.L., Ma, C., Li, J., et al.: Large-Scale patent classification with min-max modular support vector machines. In: Proceedings of the International Joint Conference on Neural Networks. IEEE, Piscataway (2008) Chu, X.L., Ma, C., Li, J., et al.: Large-Scale patent classification with min-max modular support vector machines. In: Proceedings of the International Joint Conference on Neural Networks. IEEE, Piscataway (2008)
11.
go back to reference Liu, B., Lai, M., Wu, J.L., et al.: Patent analysis and classification prediction of biomedicine industry: SOM-KPCA-SVM model. Multimed. Tools Appl. 2019, 1–21 (2019) Liu, B., Lai, M., Wu, J.L., et al.: Patent analysis and classification prediction of biomedicine industry: SOM-KPCA-SVM model. Multimed. Tools Appl. 2019, 1–21 (2019)
12.
go back to reference Choi, S., Jun, S.: Vacant technology forecasting using new bayesian patent clustering. Technol. Anal. Strateg. Manag. 26(3), 241–251 (2014)CrossRef Choi, S., Jun, S.: Vacant technology forecasting using new bayesian patent clustering. Technol. Anal. Strateg. Manag. 26(3), 241–251 (2014)CrossRef
13.
go back to reference Shanie, T., Suprijadi, J., Zulhanif: Text grouping in patent analysis using adaptive k-means clustering algorithm. In: American Institute of Physics Conference Series (2017) Shanie, T., Suprijadi, J., Zulhanif: Text grouping in patent analysis using adaptive k-means clustering algorithm. In: American Institute of Physics Conference Series (2017)
14.
go back to reference Xu, C., Peng, Z.Y., Liu, B.: Technology and effect matrix for patent clustering. In: Web Information System & Application Conference (2014) Xu, C., Peng, Z.Y., Liu, B.: Technology and effect matrix for patent clustering. In: Web Information System & Application Conference (2014)
Metadata
Title
Clustering Analysis and Visualization of TCM Patents Based on Deep Learning
Authors
Na Deng
Xu Chen
Caiquan Xiong
Copyright Year
2020
DOI
https://doi.org/10.1007/978-3-030-33506-9_46