The 15th International Conference on Advanced Data Mining and Applications (ADMA)

21-23 November, 2019, Dalian, China


Paper submission will be through the easychair.org website.

The year 2019 marks the 19th anniversary of the International Conference on Advanced Data Mining and Applications (ADMA 2019) , which will be held in Dalian, China, November 21-23, 2019. 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.

Dalian is a major city (the second largest city in Liaoning Province) and seaport in the south of Liaoning Province, China. Dalian is a popular destination among domestic tourists and foreign visitors, especially from Japan, South Korea and Russia. Its mild climate and multiple beaches as well as its importance in the modern history of China have attracted tourists. In 2007, it was one of the three cities named “China’s best tourist city”, along with Hangzhou and Chengdu, recognized by the National Tourism Administration and the United Nations World Tourism Organization [Wikipedia: https://en.wikipedia.org/wiki/Dalian].

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 2019 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,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;
12. Application of Data Mining in Education;
13. Social network data mining;
14. Smartphone data mining;
15. Database administration, indexing, performance tuning;
16. Green mining;
17. Smart Nation applications;
18. Crowdsourcing.

Submission of Papers

Paper submission will be through the easy-chair website. 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
https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines. Submissions are reviewed in a single-blind manner.

Publications

The proceedings will be published as LNAI  by Springer. They have been published since ADMA started in 2005.

Best Paper Awards

The award will be given to the paper that the Program Committee judges to be the best in quality, execution and impact among all the accepted papers in the conference.


Special Issues

High quality papers accepted by ADMA 2019 will be invited to submit an extended version for consideration of several special issues at leading international journals, including the WWWJ and the Data Science and Engineering Journal.