Identification of trends from patents using self-organizing maps

被引:31
|
作者
Segev, Aviv [1 ]
Kantola, Jussi [2 ]
机构
[1] Korea Adv Inst Sci & Technol, Dept Knowledge Serv Engn, Taejon 305701, South Korea
[2] Univ Vaasa, Dept Prod, FI-65101 Vaasa, Finland
关键词
Trend identification; Knowledge representation; Self-organizing maps;
D O I
10.1016/j.eswa.2012.05.078
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Patent users such as governments, inventors, and manufacturing organizations strive to identify the directions in which new technology is advancing, and their goal is to outline the boundaries of existing knowledge. The paper analyzes patent knowledge to identify research trends. A model based on knowledge extraction from patents and self-organizing maps for knowledge representation is presented. The model was tested on patents from the United States Patent and Trademark Office. The experiments show that the method provides both an overview of the directions of the trends and a drill-down perspective of current trends. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:13235 / 13242
页数:8
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