Conference Information

BDML 2025: International Conference on Big Data and Machine Learning

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Submission Date:
2025-11-15 Extended
Notification Date:
2025-11-25
Conference Date:
2025-12-12
Location:
Kanazawa, Japan
Years:
8
Viewed: 19131   Tracked: 7   Attend: 0

Conference Partner Index (CP-I)

47.6 / 100
Ranked #2,093 of 5,681 conferences · Top 37%

#118 of 337 in Data Mining & Databases #220 of 739 in Artificial Intelligence & Machine Learning

Academic recognition (35%) No data - scored at the neutral baseline of 50
Submission selectivity (20%) No data - scored at the neutral baseline of 50
Editions held (20%)
59
Community attention (10%)
30
Public record completeness (15%)
35

Inputs used: Editions on record: 8 · Researchers following it here: 7 · Researchers who opened this page in the past 24 months: 3

Missing from the public record: Historical acceptance rates (+4.5) · 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 45% - 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 2026-09-13

Call For Papers

BDML 2025 (International Conference on Big Data and Machine Learning) is an academic conference held in Kanazawa, Japan on 2025-12-12. The paper submission deadline is 2025-11-15 (extended). Acceptance notifications are sent on 2025-11-25.

The Program Committee invites technical papers on substantial, original, and unpublished research in active research areas that are relevant to big data and machine learning. BDML2025 welcomes contributions in areas including but not limited to: . Big Data Big Data Techniques, models and algorithms Big Data Infrastructure and platform Big Data Search and Mining Big Data Security, Privacy and Trust Big Data Applications, Bioinformatics, Multimedia etc Big Data Tools and systems Big Data Mining Big Data Management Cloud and grid computing for Big Data Machine Learning and AI for Big Data Big Data Analytics and Social Media 5G and Networks for Big Data Machine learning Machine Learning Applications Learning in knowledge-intensive systems Learning Methods and analysis Learning Problems Deep Learning Computer Vision Bayesian Network Data Mining
Last updated by Dunn Carl on

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