Call for Papers

The year 2021 marks the 17th anniversary of the International Conference on Advanced Data Mining and Applications (ADMA'21), which will be held in Sydney, Australia, 1-3 December, 2021. It is our great pleasure to invite you to contribute papers and participate in this premier annual event on research and applications of data mining.

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, bio-medical science and green computing. ADMA'21 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;
19. Deep Learning with small samples of Web Data;

Data Mining Applications:
1. Big data;
2. Web of Things;
3. Grid computing;
4. DNA sequencing, 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.

Submission Guidelines

Important Dates:

     ○    Submission deadline: 15 July 2021
     ○    Notification date: 30 Aug 2021
     ○    Camera-ready version: 20 Sep 2021
     ○    Conference dates: 1-3 Dec 2021

Formatting Guidelines:

     ○    The paper should be in English and contain unpublished contributions to the data mining and related fields.
     ○    The paper should not exceed 15 pages in LNAI (Lecture Notes in Artificial Intelligence) format.
     ○    Manuscripts must be prepared in accordance with the LNAI format.
     ○    For the template and details on the LNCS style, see Springer’s Author Instructions, click here.
     ○    Submissions are reviewed in a single-blind manner.

Paper Submission:   https://cmt3.research.microsoft.com/ADMA2021/Submission/Index       

Call for Papers

The year 2021 marks the 17th anniversary of the International Conference on Advanced Data Mining and Applications (ADMA'21), which will be held in Sydney, Australia, 2-5 December, 2021. It is our great pleasure to invite you to contribute papers and participate in this premier annual event on research and applications of data mining.

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, bio-medical science and green computing. ADMA'21 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;
19. Deep Learning with small samples of Web Data;

Data Mining Applications:
1. Big data;
2. Web of Things;
3. Grid computing;
4. DNA sequencing, 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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