Conference Information

ADMA 2026: International Conference on Advanced Data Mining and Applications

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Submission Date:
2026-05-29
Notification Date:
2026-08-03
Conference Date:
2026-11-01
Location:
Hong Kong, China
Years:
22
CCF: C   ICORE: C   QUALIS: B2   Viewed: 66378   Tracked: 36   Attend: 14

Conference Partner Index (CP-I)

71.0 / 100
Ranked #321 of 5,687 conferences · Top 6%

#20 of 337 in Data Mining & Databases

Academic recognition (35%)
68
Submission selectivity (20%)
69
Editions held (20%)
84
Community attention (10%)
68
Public record completeness (15%)
65

Inputs used: Listed as CCF C, ICORE C, QUALIS B2 · Acceptance rate: 37.7% (mean of 3 editions on file) · Editions on record: 22 · Researchers following it here: 36 · Researchers who opened this page in the past 24 months: 82

Missing from the public record: Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 100% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-29

Call For Papers

ADMA 2026 (International Conference on Advanced Data Mining and Applications) is a CCF C / ICORE C / QUALIS B2 conference held in Hong Kong, China on 2026-11-01. The paper submission deadline is 2026-05-29. Acceptance notifications are sent on 2026-08-03.

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
Last updated by Dou Sun on

Acceptance Ratio

Average acceptance rate: 37.7% over 3 years (2005–2016).

YearSubmittedAcceptedAccepted(%)
20161055653.3%
20132229643.2%
200560210016.6%

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