Advanced Data Mining and Applications (Paperback)
Quan Z. Sheng
Sold by AussieBookSeller, Truganina, VIC, Australia
AbeBooks Seller since June 22, 2007
New - Soft cover
Condition: New
Quantity: 1 available
Add to basketSold by AussieBookSeller, Truganina, VIC, Australia
AbeBooks Seller since June 22, 2007
Condition: New
Quantity: 1 available
Add to basketPaperback. 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 Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Seller Inventory # 9789819608461
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.
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