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ADMA 2021 : The 17th International Conference on Advanced Data Mining and ApplicationsConference Series : Advanced Data Mining and Applications | |||||||||||||||
Link: http://adma2021.net/ | |||||||||||||||
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Call For Papers | |||||||||||||||
The 17th International Conference on Advanced Data Mining and Applications (ADMA) 6-9 December 2021, Sydney, Australia. The conference aims at bringing together the experts on data mining from around the world and providing a leading international forum for the dissemination of original research findings in data mining, spanning applications, algorithms, software and systems, as well as different applied disciplines with potential in data mining, such as smartphone and social network mining, biomedical science and green computing. ADMA 2021 will promote the same close interaction and collaboration among practitioners and researchers. Published papers will go through a full peer-review process. We invite authors to submit papers on topics of data mining and applications, including but not limited to:
Data Mining Theory: 1. Data mining foundations; 2. Grand challenges of data mining; 3. Parallel and distributed data mining algorithms; 4. Mining on data streams; 5. Graph mining; 6. Spatial data mining; 7. Text, video, multimedia data mining; 8. Web mining; High-performance data mining algorithms; 9. Correlation mining; 10. Benchmarking and evaluations; 11. Interactive data mining; 12. Data-mining-ready structures and pre-processing; 13. Data mining visualization; 14. Information hiding in data mining; 15. Security and privacy issues; 16. Competitive analysis of mining algorithms; 17. Internet of Things mining; 18. Personalization and recommendation systems Data Mining Applications: 1. Big data; 2. Web of Things; 3. Grid computing; 4. DNA sequencing, bioinformatics, genomics, and biometrics; 5. Image interpretations; 6. E-commerce and Web services; 7. Health informatics; 8. Disaster prediction; 9. Remote monitoring; 10. Financial market analysis; 11. Online filtering; 12. Application of Data Mining in Education; 13. Social network data mining; 14. Smartphone data mining; 15. Database administration, indexing, performance tuning; 16. Green computing data mining; 17. Smart Nation applications; 18. Crowdsourcing. |
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