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A Method for Calculating Patent Similarity Using Patent Model Tree Based on Neural Network

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10989))

Abstract

To make full use of patent information and help companies find similar patent pairs by calculating the similarity of patents, help them deal with the issue of patent infringement detection, patent search, enterprise competition analysis, and patent layout, this paper proposes a method for calculation of patent similarity based on patent text using patent model tree. This method not only simplifies the process of understanding the patent text but also increases the accuracy of calculating the similarity among patents effectively. In this paper, the similarity between patents is calculated based on the patent model tree, and different similarity calculation methods are used according to different properties of tree nodes. Among them, in order to improve the accuracy of the claims node similarity measurement results, the Siamese LSTM network is applied. The experimental results show that the patent similarity calculation method based on text has an outstanding accuracy.

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Acknowledgements

The project is supported by HJSW and Research & Development plan of Shaanxi Province (Program No. 2017ZDXM-GY-094, 2015KTZDGY04-01).

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Correspondence to Tong Zhao .

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Ma, C., Zhao, T., Li, H. (2018). A Method for Calculating Patent Similarity Using Patent Model Tree Based on Neural Network. In: Ren, J., et al. Advances in Brain Inspired Cognitive Systems. BICS 2018. Lecture Notes in Computer Science(), vol 10989. Springer, Cham. https://doi.org/10.1007/978-3-030-00563-4_62

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  • DOI: https://doi.org/10.1007/978-3-030-00563-4_62

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00562-7

  • Online ISBN: 978-3-030-00563-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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