Next Article in Journal
Corporate Social Responsibility as a Strategic Means to Attract Foreign Investment: Evidence from Korea
Next Article in Special Issue
Top Management Teams’ Characteristics and Strategic Decision-Making: A Mediation of Risk Perceptions and Mental Models
Previous Article in Journal
How Do Terrestrial Determinants Impact the Response of Water Quality to Climate Drivers?—An Elasticity Perspective on the Water–Land–Climate Nexus
Previous Article in Special Issue
Big Social Network Data and Sustainable Economic Development
Article Menu
Issue 11 (November) cover image

Export Article

Open AccessArticle
Sustainability 2017, 9(11), 2117; doi:10.3390/su9112117

Developing a Methodology of Structuring and Layering Technological Information in Patent Documents through Natural Language Processing

Department of Industrial & Systems Engineering, School of Engineering, Dongguk University, 26, Pil-dong 3-ga, Chung-gu, Seoul 100-715, Korea
*
Author to whom correspondence should be addressed.
Received: 15 September 2017 / Revised: 6 November 2017 / Accepted: 13 November 2017 / Published: 17 November 2017
View Full-Text   |   Download PDF [1391 KB, uploaded 17 November 2017]   |  

Abstract

Since patents contain various types of objective technological information, they are used to identify the characteristics of technology fields. Text mining in patent analysis is employed in various fields such as trend analysis and technology classification, and knowledge flow among technologies. However, since keyword-based text mining has the limitation whereby, when screening useful keywords, it frequently omits meaningful keywords, analyzers therefore need to repeat the careful scrutiny of the derived keywords to clarify the meaning of keywords. In this research, we structure meaningful keyword sets related to technological information from patent documents; then we layer the keywords, depending on the level of information. This research involves two steps. First, the characteristics of technological information are analyzed by reviewing the patent law and investigating the description of patent documents. Second, the technological information is structured by considering the information types, and the keywords in each type are layered through natural language processing. Consequently, the structured and layered keyword set does not omit useful keywords and the analyzer can easily understand the meaning of each keyword. View Full-Text
Keywords: text mining; NLP; technological information; patent analysis; text structure text mining; NLP; technological information; patent analysis; text structure
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Roh, T.; Jeong, Y.; Yoon, B. Developing a Methodology of Structuring and Layering Technological Information in Patent Documents through Natural Language Processing. Sustainability 2017, 9, 2117.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sustainability EISSN 2071-1050 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top