基于专利结构的中文专利摘要研究  

Research on Chinese Patent Summarization Based on Patented Structure

作　　者：束云峰 王中卿[1] SHU Yun-feng;WANG Zhong-qing(School of Computer Science and Technology,Soochow University,Suzhou,Jiangsu 215006,China)

机构地区：[1]苏州大学计算机科学与技术学院,江苏苏州215006

出　　处：《计算机科学》2020年第S01期45-48,共4页Computer Science

基　　金：国家自然科学基金(61806137,61702518)。

摘　　要：任务旨在通过对原文进行压缩提炼,得出简明扼要的内容描述。针对中文专利文本,提出了一种基于Patent-Rank算法生成专利摘要的算法。首先,对候选句群做冗余处理,以去除候选句群中相似度较高的句子;然后,对专利中的权利要求书和说明书构建3种不同的相似度计算方法,以计算句子之间的影响权重;最后,选取权值高的句子输出,并将其作为专利的摘要。该算法在选取的数据集中取得了较好的效果。实验结果表明提出的算法相比于已有方法在ROUGE值上有显著提高。Text summarization aims to provide a concise description of the content by compressing and refining the original text.For the Chinese patented text,an algorithm for generating patent summarization based on the PatentRank algorithm is proposed.Firstly,the candidate sentence groups are redundantly processed to remove the sentences with high similarity in the candidate sentence groups.Then,three different similarity calculation methods are constructed for the patent claims and descriptions to calculate the weights between sentences.Finally,the sentence with high weight is selected as the summarization of the patent.The algorithm has achieved good results in the selected datasets.Experimental results demonstrate that the proposed method substantially outperforms existing approaches in terms of ROUGE measurement.

关 键 词：文本摘要 专利 相似度计算 中文信息处理 PatentRank 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]