Intelligent Data Engineering and Automated Learning – IDEAL 2024
| dc.contributor.author | Nogueira, Vitor | |
| dc.contributor.editor | Julian, Vicente | |
| dc.contributor.editor | Camacho, David | |
| dc.contributor.editor | Yin, Hujun | |
| dc.contributor.editor | Nogueira, Vitor | |
| dc.contributor.editor | Novais, Paulo | |
| dc.contributor.editor | Tallón-Ballesteros, Antonio | |
| dc.date.accessioned | 2026-02-23T11:19:38Z | |
| dc.date.available | 2026-02-23T11:19:38Z | |
| dc.date.issued | 2024-11 | |
| dc.description.abstract | This two-volume set, LNCS 15346 and LNCS 15347, constitutes the proceedings of the 25th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2024, held in Valencia, Spain, during November 20–22, 2024. The 86 full papers and 6 short papers presented in this book were carefully reviewed and selected from 130 submissions. IDEAL 2024 is focusing on Big Data Analytics and Privacy, Machine Learning & Deep Learning for Real-World Applications, Data Mining and Pattern Recognition, Information Retrieval and Management, Bio and Neuro-Informatics, and Hybrid Intelligent Systems and Agents. | por |
| dc.identifier.authorbook | nao | por |
| dc.identifier.authoremail | vbn@uevora.pt | |
| dc.identifier.doi | https://doi.org/10.1007/978-3-031-77738-7 | por |
| dc.identifier.editorbook | nao | por |
| dc.identifier.scientificarea | 498 | por |
| dc.identifier.uri | https://link.springer.com/book/10.1007/978-3-031-77738-7?sap-outbound-id=8E60A3B322685E0644F6A6F4D74D9C63B6CFFD48&utm_source=standard&utm_medium=email&utm_campaign=000_LAN36_0000019083_Book+author+congrats+NEW&utm_content=EN_34155_20241124&mkt-key=42010A0550671EDAA6EA4E53A0E28D99 | |
| dc.identifier.uri | http://hdl.handle.net/10174/41362 | |
| dc.language.iso | eng | por |
| dc.publisher | Springer Cham | por |
| dc.rights | restrictedAccess | por |
| dc.subject | Data Mining and Knowledge | por |
| dc.subject | Machine Learning | por |
| dc.title | Intelligent Data Engineering and Automated Learning – IDEAL 2024 | por |
| dc.type | book |