Item Infomation
Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Thimm, Heiko | - |
| dc.date.accessioned | 2023-08-04T04:34:46Z | - |
| dc.date.available | 2023-08-04T04:34:46Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.uri | https://link.springer.com/article/10.1007/s10669-023-09900-7 | - |
| dc.identifier.uri | https://dlib.phenikaa-uni.edu.vn/handle/PNK/8672 | - |
| dc.description | CC-BY | vi |
| dc.description.abstract | The constantly growing body of global environmental legislation necessitates that corporate environmental compliance managers frequently assess the relevance of new regulations and regulation revisions for each of their sites. Companies are pressured to streamline and automate this crucial task through digital workflows and specialized IT-based assistance systems. This has recently piqued the interest of researchers working in different disciplines, such as intelligent systems, machine learning, and natural language processing. The article describes the latest results of our long-term research program on IT-based support for corporate compliance management, offering insights for these, and other disciplines. The context and the main aspects of environmental regulation announcements and the relevance assessment task are analyzed. | vi |
| dc.language.iso | en | vi |
| dc.publisher | Springer | vi |
| dc.subject | specialized IT-based assistance systems | vi |
| dc.subject | NLP-based scoring method | vi |
| dc.title | Data modeling and NLP-based scoring method to assess the relevance of environmental regulatory announcements | vi |
| dc.type | Book | vi |
| Appears in Collections | ||
| OER - Khoa học môi trường | ||
Files in This Item:
