A Hybrid Method of Analyzing Patents for Sustainable Technology Management in Humanoid Robot Industry
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Jongchan | - |
dc.contributor.author | Lee, Joonhyuck | - |
dc.contributor.author | Kim, Gabjo | - |
dc.contributor.author | Park, Sangsung | - |
dc.contributor.author | Jang, Dongsik | - |
dc.date.accessioned | 2021-09-04T00:13:42Z | - |
dc.date.available | 2021-09-04T00:13:42Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2016-05 | - |
dc.identifier.issn | 2071-1050 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/88806 | - |
dc.description.abstract | A humanoid, which refers to a robot that resembles a human body, imitates a human's intelligence, behavior, sense, and interaction in order to provide various types of services to human beings. Humanoids have been studied and developed constantly in order to improve their performance. Humanoids were previously developed for simple repetitive or hard work that required significant human power. However, intelligent service robots have been developed actively these days to provide necessary information and enjoyment; these include robots manufactured for home, entertainment, and personal use. It has become generally known that artificial intelligence humanoid technology will significantly benefit civilization. On the other hand, Successful Research and Development (R & D) on humanoids is possible only if they are developed in a proper direction in accordance with changes in markets and society. Therefore, it is necessary to analyze changes in technology markets and society for developing sustainable Management of Technology (MOT) strategies. In this study, patent data related to humanoids are analyzed by various data mining techniques, including topic modeling, cross-impact analysis, association rule mining, and social network analysis, to suggest sustainable strategies and methodologies for MOT. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | MDPI | - |
dc.subject | CROSS IMPACT ANALYSIS | - |
dc.subject | INFORMATION | - |
dc.title | A Hybrid Method of Analyzing Patents for Sustainable Technology Management in Humanoid Robot Industry | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Park, Sangsung | - |
dc.contributor.affiliatedAuthor | Jang, Dongsik | - |
dc.identifier.doi | 10.3390/su8050474 | - |
dc.identifier.scopusid | 2-s2.0-84970950210 | - |
dc.identifier.wosid | 000377983800068 | - |
dc.identifier.bibliographicCitation | SUSTAINABILITY, v.8, no.5 | - |
dc.relation.isPartOf | SUSTAINABILITY | - |
dc.citation.title | SUSTAINABILITY | - |
dc.citation.volume | 8 | - |
dc.citation.number | 5 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
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 | CROSS IMPACT ANALYSIS | - |
dc.subject.keywordPlus | INFORMATION | - |
dc.subject.keywordAuthor | sustainable technology management | - |
dc.subject.keywordAuthor | humanoid | - |
dc.subject.keywordAuthor | cross-impact analysis | - |
dc.subject.keywordAuthor | topic model | - |
dc.subject.keywordAuthor | patents | - |
dc.subject.keywordAuthor | network analysis | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea 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.