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공공누리This item is licensed Korea Open Government License

dc.contributor.author
김진형
dc.contributor.author
정도헌
dc.contributor.author
정한민
dc.contributor.author
황명권
dc.date.accessioned
2019-08-28T07:41:05Z
dc.date.available
2019-08-28T07:41:05Z
dc.date.issued
2012-05-17
dc.identifier.issn
0957-4174
dc.identifier.uri
https://repository.kisti.re.kr/handle/10580/13995
dc.description.abstract
Analyzingmassinformationandsupportingforesightareveryimportanttaskbuttheyareextremely
time-consumingwork.Inaddition,informationanalysisandforecastingaboutthescienceandtechnology
arealsoverycriticaltasksforresearchers,governmentofficers,businessman,etc.Somerelatedstudies
recentlyhavebeenexecutedandsemi-automatictoolshavebeendevelopedactively.Many
researchers,annalists,andbusinessmenalsogenerallyusethosetoolsforstrategicdecisionmaking.
However,existingprojectsandtoolsarebasedonsubjectiveopinionsfromseveralexpertsandmost
oftoolssimplyexplaincurrentsituations,notforecastingnearfuturetrends.Therefore,inthispaper,
weproposeatechnologytrendsanalysisandforecastingmodelbasedonquantitativeanalysisandseveral
textminingtechnologiesforeffective,systematic,andobjectiveinformationanalysisandforecasting
technologytrends.Additionally,weexecuteacomparativeevaluationbetweenthesuggestedmodeland
Gartner’sforecastingmodelforvalidatingthesuggestedmodelbecausetheGartner’smodeliswidelyand
generallyusedforinformationanalysisandforecasting.
dc.language
eng
dc.relation.ispartofseries
ExpertSystemswithApplications
dc.title
Technology trends analysis and forecasting application based on decision tree and statiscial feature analysis
dc.citation.endPage
12625
dc.citation.number
1
dc.citation.startPage
12618
dc.citation.volume
39
dc.subject.keyword
Technologytrendsanalysis
dc.subject.keyword
technologytrendsforecasting
dc.subject.keyword
featureanalysis
dc.subject.keyword
decisionmaking
dc.subject.keyword
strategicintelligence
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7. KISTI 연구성과 > 학술지 발표논문
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