Methods of Russian Patent Analysis

D. Korobkin, S. Vasiliev, S. Fomenkov, S. Kolesnikov
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Abstract

The article presents a method for extracting predicate-argument constructions characterizing the composition of the structural elements of the inventions and the relationships between them. The extracted structures are converted into a domain ontology and used in prior art patent search and information support of automated invention. The analysis of existing natural language processing (NLP) tools in relation to the processing of Russian-language patents has been carried out. A new method for extracting structured data from patents has been proposed taking into account the specificity of the text of patents and is based on the shallow parsing and segmentation of sentences. The value of the F1 metric for a rigorous estimate of data extraction is 63% and for a lax estimate is 79%. The results obtained suggest that the proposed method is promising.
俄罗斯专利分析方法
本文提出了一种提取表征发明结构要素组成及其相互关系的谓词-论证结构的方法。将提取的结构转化为领域本体,用于现有技术专利检索和自动化发明的信息支持。对现有的与俄语专利处理相关的自然语言处理(NLP)工具进行了分析。考虑到专利文本的特殊性,提出了一种基于句子浅层解析和分词的专利结构化数据提取方法。对于数据提取的严格估计,F1指标的值为63%,对于宽松估计,F1指标的值为79%。结果表明,该方法是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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