Abstract
Patents contain a lot of technical, economic and legal information, and they are the main references of enterprises’ technological innovation. As a tool of patent analysis and mining, technology/effect matrix provides important support for technological innovation and avoidance. In the process of building technology/effect matrix, most of current technical efficiency annotation is by manually work, which requires heavy labor. Considering the distribution and morphological characteristics of patent abstract texts, this paper proposes a multi-features fused scoring algorithm named PaEffExtr, which automatically extracts effect statements from patent abstract texts. The experimental results show that the algorithm has good recall and accuracy.
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Acknowledgments
This paper was supported by Research Foundation for Advanced Talents of Hubei University of Technology (No. BSQD12131), the Fundamental Research Funds for the Young Teachers’ Innovation project of Zhongnan University of Economics and Law (No. 2014147), the Educational Commission of Hubei Province of China (No. D20151401) and the Green Industry Technology Leading Project of Hubei University of Technology (No. ZZTS2017006).
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Deng, N., Chen, X., Ruan, O., Wang, C., Ye, Z., Tian, J. (2018). PaEffExtr: A Method to Extract Effect Statements Automatically from Patents. In: Barolli, L., Terzo, O. (eds) Complex, Intelligent, and Software Intensive Systems. CISIS 2017. Advances in Intelligent Systems and Computing, vol 611. Springer, Cham. https://doi.org/10.1007/978-3-319-61566-0_62
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DOI: https://doi.org/10.1007/978-3-319-61566-0_62
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