Cited 13 time in
Identifying Promising Research Frontiers of Pattern Recognition through Bibliometric Analysis
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Park, Inchae | - |
| dc.contributor.author | Yoon, Byungun | - |
| dc.date.accessioned | 2024-08-08T03:30:45Z | - |
| dc.date.available | 2024-08-08T03:30:45Z | - |
| dc.date.issued | 2018-11 | - |
| dc.identifier.issn | 2071-1050 | - |
| dc.identifier.issn | 2071-1050 | - |
| dc.identifier.uri | https://scholarworks.dongguk.edu/handle/sw.dongguk/16961 | - |
| dc.description.abstract | This paper aims at proposing a quantitative methodology to identify promising research frontiers (RFs) based on bibliographic information of scientific papers and patents. To achieve this, core technological documents are identified by suggesting several indices which measure paper impact, research impact, patent novelty, impact, marketability, and the right range to evaluate technological documents and which measure the research capability of research organizations (ROs) such as a RO's activity, productivity, market competitiveness, and publication impact. The RFs can be identified by clustering core technological documents, and promising indices of each RF which are from the perspectives of growth, impact, marketability, and science-based effect, are calculated to promising RFs. As an illustration, this paper selects the case of pattern recognition technology among various technologies in the information and communication technology sector. To validate the proposed method, emerging technologies on the hype cycle are utilized, allowing analysts to compare the results. Comparing the results derived from scientific papers and patents, the results from scientific papers are proper to suggest themes for research (R) in relatively long-term perspective, whereas the results from patents are appropriate for providing themes for development (D) in terms of relatively short-term view. This approach can assist research organizations and companies in devising a technology strategy for a future direction of research and development. | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | MDPI | - |
| dc.title | Identifying Promising Research Frontiers of Pattern Recognition through Bibliometric Analysis | - |
| dc.type | Article | - |
| dc.publisher.location | 스위스 | - |
| dc.identifier.doi | 10.3390/su10114055 | - |
| dc.identifier.scopusid | 2-s2.0-85055972725 | - |
| dc.identifier.wosid | 000451531700229 | - |
| dc.identifier.bibliographicCitation | SUSTAINABILITY, v.10, no.11 | - |
| dc.citation.title | SUSTAINABILITY | - |
| dc.citation.volume | 10 | - |
| dc.citation.number | 11 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | ssci | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
| dc.relation.journalResearchArea | Environmental Sciences & Ecology | - |
| dc.relation.journalWebOfScienceCategory | Green & Sustainable Science & Technology | - |
| dc.relation.journalWebOfScienceCategory | Environmental Sciences | - |
| dc.relation.journalWebOfScienceCategory | Environmental Studies | - |
| dc.subject.keywordPlus | EMERGING TECHNOLOGIES | - |
| dc.subject.keywordPlus | INFORMATION | - |
| dc.subject.keywordPlus | SCIENCE | - |
| dc.subject.keywordPlus | EVOLUTION | - |
| dc.subject.keywordPlus | CITATION | - |
| dc.subject.keywordPlus | NETWORK | - |
| dc.subject.keywordPlus | SYSTEM | - |
| dc.subject.keywordAuthor | promising technology | - |
| dc.subject.keywordAuthor | research frontier | - |
| dc.subject.keywordAuthor | bibliometric analysis | - |
| dc.subject.keywordAuthor | hype cycle | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
30, Pildong-ro 1-gil, Jung-gu, Seoul, 04620, Republic of Korea+82-2-2260-3114
Copyright(c) 2023 DONGGUK UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.
