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- Kim, Sungil
- Data Analytics Lab.
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| DC Field | Value | Language |
|---|---|---|
| dc.citation.conferencePlace | KO | - |
| dc.citation.conferencePlace | 서울대학교 | - |
| dc.citation.title | 대한산업공학회 2019 추계학술대회 | - |
| dc.contributor.author | 오용경 | - |
| dc.contributor.author | 김성일 | - |
| dc.date.accessioned | 2024-01-31T23:36:05Z | - |
| dc.date.available | 2024-01-31T23:36:05Z | - |
| dc.date.created | 2019-12-18 | - |
| dc.date.issued | 2019-11-08 | - |
| dc.identifier.bibliographicCitation | 대한산업공학회 2019 추계학술대회 | - |
| dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/78902 | - |
| dc.publisher | 대한산업공학회 | - |
| dc.title | Exploiting Logistics Anomaly Detection using Maritime Big Data | - |
| dc.type | Conference Paper | - |
| dc.date.conferenceDate | 2019-11-08 | - |
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