Advanced Data Mining and Applications (Paperback)

Quan Z. Sheng

ISBN 10: 9819608465 / ISBN 13: 9789819608461

Published by Springer Nature Switzerland AG, Cham, 2024

About this Item

Paperback. This six-volume set, LNAI 15387-15392, constitutes the refereed proceedings of the 20th International Conference on Advanced Data Mining and Applications, ADMA 2024, held in Sydney, New South Wales, Australia, during December 35, 2024.The 159 full papers presented here were carefully reviewed and selected from 422 submissions. These papers have been organized under the following topical sections across the different volumes: -Part I : Applications; Data mining.Part II : Data mining foundations and algorithms; Federated learning; Knowledge graph.Part III : Graph mining; Spatial data mining.Part IV : Health informatics.Part V : Multi-modal; Natural language processing.Part VI : Recommendation systems; Security and privacy issues. This six-volume set, LNAI 15387-15392, constitutes the refereed proceedings of the 20th International Conference on Advanced Data Mining and Applications, ADMA 2024, held in Sydney, New South Wales, Australia, during December 35, 2024.The 159 full papers presented here were carefully reviewed and selected from 422 submissions. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9789819608461

Bibliographic Details

Title: Advanced Data Mining and Applications (...

Publisher: Springer Nature Switzerland AG, Cham

Publication Date: 2024

Binding: Paperback

Condition: new

About this title

Synopsis:

This six-volume set, LNAI 15387-15392, constitutes the refereed proceedings of the 20th International Conference on Advanced Data Mining and Applications, ADMA 2024, held in Sydney, New South Wales, Australia, during December 3–5, 2024.

The 159 full papers presented here were carefully reviewed and selected from 422 submissions. These papers have been organized under the following topical sections across the different volumes: -

Part I : Applications; Data mining.

Part II : Data mining foundations and algorithms; Federated learning; Knowledge graph.

Part III : Graph mining; Spatial data mining.

Part IV : Health informatics.

Part V : Multi-modal; Natural language processing.

Part VI : Recommendation systems; Security and privacy issues.