
۳۰ مهر - ۰۲ آبان ۱۴۰۴
International Conference on Advanced Data Mining and Applications
هنوز دنبالکنندهای وجود ندارد.
نمای کلی
The 21st International Conference on Advanced Data Mining and Applications (ADMA2025) will be held in Kyoto, Japan, from October 22 to 24, 2025. The conference aims to be a leading international forum for disseminating original research findings in data mining, spanning applications, algorithms, software, and systems. Accepted papers will be published by Springer in LNAI (Lecture Notes in Artificial Intelligence) and indexed in EI and DBLP.
ADMA2025: Call for Research and Industry Papers
The 21st International Conference on Advanced Data Mining and Applications (ADMA2025) will be held in Kyoto, Japan, October 22-24, 2025. We invite authors to contribute papers and participate in this premier annual event on research and applications of data mining.
Themes and Topics
We invite authors to submit papers relevant to the topics include, but are not limited to:
- Data Mining Theories and Technologies
- Data mining foundations and algorithms
- Grand challenges in big data mining
- Mining on data streams
- Graph mining
- Spatial and temporal data mining
- Text, video, multimedia data mining
- Web mining and social networks
- Correlation mining and causality analysis
- Recommender systems
- Generative data mining
- Deep learning models for data mining
- Trustworthy and responsible data mining
- Data mining security and privacy
- Federated and privacy-aware data mining
- Parallel and distributed data mining
- Interactive data mining and visualisation
- Benchmarking and evaluations
- Trends in advanced data mining
- Data Mining Applications
- Data mining for edge intelligence
- Data mining for bioinformatics
- Image mining & interpretations
- E-commerce data mining
- Healthcare informatics
- Disaster prediction and prevention
- Data Mining Applications with LLMs
- Financial market analysis
- Software analysis with data mining
- Data mining enhanced education
- Data mining for AgriTech
- Data mining in Internet of Things
- Mining for database management
- Data mining for space science
- Data mining for cyber security
- Data mining for eScience
- Smart Cities applications
- Data mining for societal science
Submission Categories
ADMA 2025 has three submission tracks: Research Track, Industry Track, and Special Session Track. All track submissions must follow the LNAI (Lecture Notes in Artificial Intelligence) format. Papers must not exceed 15 pages (including references).
- Research Track: Submissions will undergo double-blind peer review. Focuses on original research in data mining, covering applications, algorithms, software, and systems. Contributions should advance theoretical or applied data mining.
- Industry Track: Submissions will undergo single-blind peer review. Focuses on applied research and real-world implementations. Submissions should highlight practical value, industrial significance, and innovative deployments.
- Special Session Track: Please refer to the corresponding webpages on the ADMA 2025 website for details.
The ADMA is recognized as a C-level conference by CCF (China Computer Federation).
Important Dates (AoE Time)
- Research Paper Submission Deadline: June 5, 2025
- Industry Paper Submission Deadline: June 12, 2025
- Special Session Paper Submission Deadline: June 5, 2025
- Paper Notification (All Tracks): August 17, 2025
- Camera-Ready Submission Deadline (All Tracks): August 24, 2025
- Conference Dates: October 22 to 24, 2025
Submission Guidelines
Submission Site
The peer-review process is managed through Microsoft CMT: https://cmt3.research.microsoft.com/ADMA2025
Formatting Guidelines
- Papers must be in English and contain unpublished contributions.
- Manuscripts must adhere to the LNAI format. Templates and formatting details are available in Springer's Author Instructions.
- The paper should NOT exceed 15 pages in LNAI format.
Double-Blind Submission Policy
- Author identities and affiliations are not disclosed to reviewers.
- Authors must submit PDFs without author names and affiliations, and without metadata revealing identities.
- Avoid directly reusing text or figures from prior publications without proper attribution.
- Do not include acknowledgements or funding details that could reveal identity or affiliation.
Supplementary Materials
- May be submitted separately in a single file (ZIP or PDF, within 20MB).
- Do NOT reveal any author identity or affiliation information in supplementary materials.
- There is no page limit for supplementary materials.
- Deadline for supplementary materials: Research/Special Session Tracks - June 8, 2025; Industry Track - June 15, 2025.
Dual Submission Policy
Submissions must not be under review or accepted for publication elsewhere. Dual submissions to archival venues are strictly prohibited.
Own Prior Work, Well-Known Projects, and Research Artifacts
- Do not upload manuscripts to preprint servers or personal websites while under review. If a prior version exists, it must be blinded, and the existence must be disclosed to the Program Chair.
- Any violation of these rules may result in desk rejection.
Conflicts of Interest (COI)
Authors must flag conflicts with Program Committee members in CMT. Conflicts include:
- Working at the same university/company in the past two years or next six months.
- Co-authorship or collaboration within the last three years.
- Advisor/advisee relationship (regardless of time).
- Being a relative or close personal friend.
Failure to declare conflicts may result in desk rejection.
Contact Us
- Email: adma2025-committee@googlegroups.com
- Twitter: @ADMA2025
تاریخهای کنفرانس
Conference Date
۳۰ مهر ۱۴۰۴ → ۲ آبان ۱۴۰۴
ارسال مقاله
Special Session Proposal Submission Deadline
۲۵ اسفند ۱۴۰۳
Research Paper Submission Deadline
۱۵ خرداد ۱۴۰۴
Industry Paper Submission Deadline
۲۲ خرداد ۱۴۰۴
اعلان
Tutorial Proposal Notification
۱۹ مرداد ۱۴۰۴
Short Paper Notification
۲۳ مرداد ۱۴۰۴
Paper Notification (All Tracks)
۲۶ مرداد ۱۴۰۴
نسخه نهایی
Camera-Ready Submission Deadline (All Tracks)
۲ شهریور ۱۴۰۴
رتبه منبع
منبع: CORE2023
رتبه: C
حوزه پژوهشی: Data management and data science, Machine learning