Bibliometric analysis of patent infringement retrieval model based on self-organizing map neural network algorithm

被引：11

作者：

Zhu, Dimin ^{[1
]}

机构：

[1] Zhejiang Gongshang Univ, Coll Commerce, Hangzhou, Zhejiang, Peoples R China

来源：

LIBRARY HI TECH | 2020年 / 38卷 / 02期

关键词：

Databases; Data analysis; Data mining; Social sciences; Data collection techniques; Hypertext; FUZZY C-MEANS; CLASSIFICATION;

D O I：

10.1108/LHT-12-2018-0201

中图分类号：

G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];

学科分类号：

1205 ; 120501 ;

摘要：

Purpose The purpose of this paper is to quickly retrieve the same or similar patents in a large patent database. Design/methodology/approach The research is carried out through the analysis of the issue of patent examination, the type of patent infringement search and theories related to patent infringement determination and text mining. Findings The results show that the model improves the speed of patent search. It can quickly, accurately and comprehensively retrieve the same or equivalent patents as the imported patent claims. Originality/value This study has great significance for improving the efficiency of patent examiners.

引用

页码：479 / 491

页数：13

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