Matches in SemOpenAlex for { <https://semopenalex.org/work/W2095602233> ?p ?o ?g. }
Showing items 1 to 82 of
82
with 100 items per page.
- W2095602233 endingPage "12625" @default.
- W2095602233 startingPage "12618" @default.
- W2095602233 abstract "Analyzing mass information and supporting foresight are very important task but they are extremely time-consuming work. In addition, information analysis and forecasting about the science and technology are also very critical tasks for researchers, government officers, businessman, etc. Some related studies recently have been executed and semi-automatic tools have been developed actively. Many researchers, annalists, and businessmen also generally use those tools for strategic decision making. However, existing projects and tools are based on subjective opinions from several experts and most of tools simply explain current situations, not forecasting near future trends. Therefore, in this paper, we propose a technology trends analysis and forecasting model based on quantitative analysis and several text mining technologies for effective, systematic, and objective information analysis and forecasting technology trends. Additionally, we execute a comparative evaluation between the suggested model and Gartner’s forecasting model for validating the suggested model because the Gartner’s model is widely and generally used for information analysis and forecasting." @default.
- W2095602233 created "2016-06-24" @default.
- W2095602233 creator A5037898363 @default.
- W2095602233 creator A5038598860 @default.
- W2095602233 creator A5081103879 @default.
- W2095602233 creator A5085683467 @default.
- W2095602233 date "2012-11-01" @default.
- W2095602233 modified "2023-09-28" @default.
- W2095602233 title "Technology trends analysis and forecasting application based on decision tree and statistical feature analysis" @default.
- W2095602233 cites W1963588453 @default.
- W2095602233 cites W1963879048 @default.
- W2095602233 cites W1969392438 @default.
- W2095602233 cites W1971091947 @default.
- W2095602233 cites W197550014 @default.
- W2095602233 cites W2030894524 @default.
- W2095602233 cites W2037219885 @default.
- W2095602233 cites W2074856671 @default.
- W2095602233 cites W2087900455 @default.
- W2095602233 doi "https://doi.org/10.1016/j.eswa.2012.05.021" @default.
- W2095602233 hasPublicationYear "2012" @default.
- W2095602233 type Work @default.
- W2095602233 sameAs 2095602233 @default.
- W2095602233 citedByCount "52" @default.
- W2095602233 countsByYear W20956022332012 @default.
- W2095602233 countsByYear W20956022332013 @default.
- W2095602233 countsByYear W20956022332014 @default.
- W2095602233 countsByYear W20956022332015 @default.
- W2095602233 countsByYear W20956022332016 @default.
- W2095602233 countsByYear W20956022332017 @default.
- W2095602233 countsByYear W20956022332018 @default.
- W2095602233 countsByYear W20956022332019 @default.
- W2095602233 countsByYear W20956022332020 @default.
- W2095602233 countsByYear W20956022332021 @default.
- W2095602233 countsByYear W20956022332022 @default.
- W2095602233 crossrefType "journal-article" @default.
- W2095602233 hasAuthorship W2095602233A5037898363 @default.
- W2095602233 hasAuthorship W2095602233A5038598860 @default.
- W2095602233 hasAuthorship W2095602233A5081103879 @default.
- W2095602233 hasAuthorship W2095602233A5085683467 @default.
- W2095602233 hasConcept C127413603 @default.
- W2095602233 hasConcept C154945302 @default.
- W2095602233 hasConcept C161657586 @default.
- W2095602233 hasConcept C201995342 @default.
- W2095602233 hasConcept C2522767166 @default.
- W2095602233 hasConcept C2780451532 @default.
- W2095602233 hasConcept C41008148 @default.
- W2095602233 hasConcept C42475967 @default.
- W2095602233 hasConcept C539667460 @default.
- W2095602233 hasConcept C64848388 @default.
- W2095602233 hasConcept C84525736 @default.
- W2095602233 hasConceptScore W2095602233C127413603 @default.
- W2095602233 hasConceptScore W2095602233C154945302 @default.
- W2095602233 hasConceptScore W2095602233C161657586 @default.
- W2095602233 hasConceptScore W2095602233C201995342 @default.
- W2095602233 hasConceptScore W2095602233C2522767166 @default.
- W2095602233 hasConceptScore W2095602233C2780451532 @default.
- W2095602233 hasConceptScore W2095602233C41008148 @default.
- W2095602233 hasConceptScore W2095602233C42475967 @default.
- W2095602233 hasConceptScore W2095602233C539667460 @default.
- W2095602233 hasConceptScore W2095602233C64848388 @default.
- W2095602233 hasConceptScore W2095602233C84525736 @default.
- W2095602233 hasIssue "16" @default.
- W2095602233 hasLocation W20956022331 @default.
- W2095602233 hasOpenAccess W2095602233 @default.
- W2095602233 hasPrimaryLocation W20956022331 @default.
- W2095602233 hasRelatedWork W1920652846 @default.
- W2095602233 hasRelatedWork W2064050250 @default.
- W2095602233 hasRelatedWork W2081647779 @default.
- W2095602233 hasRelatedWork W2783394673 @default.
- W2095602233 hasRelatedWork W2800427372 @default.
- W2095602233 hasRelatedWork W2966702294 @default.
- W2095602233 hasRelatedWork W3006892881 @default.
- W2095602233 hasRelatedWork W4237750775 @default.
- W2095602233 hasRelatedWork W51313852 @default.
- W2095602233 hasRelatedWork W428794814 @default.
- W2095602233 hasVolume "39" @default.
- W2095602233 isParatext "false" @default.
- W2095602233 isRetracted "false" @default.
- W2095602233 magId "2095602233" @default.
- W2095602233 workType "article" @default.