STNLTP: Generating Chinese Patent Abstracts Based on Integrated Strategy
Zhang Le,Du Yifan,Lü Xueqiang(),Dong Zhian
Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing Information Science and Technology University, Beijing 100101, China
[Objective] This paper proposes an abstracting model for Chinese patents based on integration strategy (STNLTP), aiming to reduce the duplication and long document dependency issues of the existing automatic abstracting techniques. [Methods] First, we introduced a patent term dictionary, and used the sememe vector based on SAT model to represent traditional Chinese medicine patents. Then, with the help of integration strategy, we utilized the TextRank, Lead4 and NMF models to extract key sentences from the patents. Third, we identified the optimal key sentences with the clustering and redundancy removing. Finally, we processed these optimal key sentences with the pointer-generator network based on Transformer character vector to create the abstracts. [Results] Our new model successfully combined the extractive and generative methods. Compared with the existing RLCPAR model, we improved the evaluation indicators of ROUGE-1, ROUGE-2 and ROUGE-L by 2.00%, 9.73% and 2.35%, respectively. [Limitations] There are still some errors in the new abstracts. [Conclusions] The new STNLTP model could effectively generate Chinese patent abstracts.
张乐, 杜一凡, 吕学强, 董志安. STNLTP:一种基于集成策略的中文专利摘要生成模型*[J]. 数据分析与知识发现, 2022, 6(7): 107-117.
Zhang Le, Du Yifan, Lü Xueqiang, Dong Zhian. STNLTP: Generating Chinese Patent Abstracts Based on Integrated Strategy. Data Analysis and Knowledge Discovery, 2022, 6(7): 107-117.
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