Technical Analysis of Data-Centric and Model-Centric Artificial Intelligence
DC Field | Value | Language |
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dc.contributor.author | Majeed, Abdul | - |
dc.contributor.author | Hwang, Seong Oun | - |
dc.date.accessioned | 2024-03-19T12:30:27Z | - |
dc.date.available | 2024-03-19T12:30:27Z | - |
dc.date.issued | 2023-11 | - |
dc.identifier.issn | 1520-9202 | - |
dc.identifier.issn | 1941-045X | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/90746 | - |
dc.description.abstract | The artificial intelligence (AI) field is going through a dramatic revolution in terms of new horizons for research and real-world applications, but some research trajectories in AI are becoming detrimental over time. Recently, there has been a growing call in the AI community to combat a dominant research trend named model-centric AI (MC-AI), which only fiddles with complex AI codes/algorithms. MC-AI may not yield desirable results when applied to real-life problems like predictive maintenance due to limited or poor-quality data. In contrast, a relatively new paradigm named data-centric (DC-AI) is becoming more popular in the AI community. In this article, we discuss and compare MC-AI and DC-AI in terms of basic concepts, working mechanisms, and technical differences. Then, we highlight the potential benefits of the DC-AI approach to foster further research on this recent paradigm. This pioneering work on DC-AI and MC-AI can pave the way to understand the fundamentals and significance of these two paradigms from a broader perspective. | - |
dc.format.extent | 9 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | IEEE COMPUTER SOC | - |
dc.title | Technical Analysis of Data-Centric and Model-Centric Artificial Intelligence | - |
dc.type | Article | - |
dc.identifier.wosid | 001167350100013 | - |
dc.identifier.doi | 10.1109/MITP.2023.3322410 | - |
dc.identifier.bibliographicCitation | IT PROFESSIONAL, v.25, no.6, pp 62 - 70 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.scopusid | 2-s2.0-85184006902 | - |
dc.citation.endPage | 70 | - |
dc.citation.startPage | 62 | - |
dc.citation.title | IT PROFESSIONAL | - |
dc.citation.volume | 25 | - |
dc.citation.number | 6 | - |
dc.type.docType | Article | - |
dc.publisher.location | 미국 | - |
dc.subject.keywordAuthor | Analytical models | - |
dc.subject.keywordAuthor | Market research | - |
dc.subject.keywordAuthor | Trajectory | - |
dc.subject.keywordAuthor | Artificial intelligence | - |
dc.subject.keywordAuthor | Predictive maintenance | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Software Engineering | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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