A1 Refereed original research article in a scientific journal
Identification of trends from patents using self-organizing maps
Authors: Segev A, Kantola J
Publisher: PERGAMON-ELSEVIER SCIENCE LTD
Publication year: 2012
Journal: Expert Systems with Applications
Journal name in source: EXPERT SYSTEMS WITH APPLICATIONS
Journal acronym: EXPERT SYST APPL
Volume: 39
Issue: 18
First page : 13235
Last page: 13242
Number of pages: 8
ISSN: 0957-4174
DOI: https://doi.org/10.1016/j.eswa.2012.05.078
Abstract
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.
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.
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