Conference Information

IDEAL 2026: International Conference on Intelligent Data Engineering and Automated Learning

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Submission Date:
2026-07-24 Extended
Notification Date:
2026-09-01
Conference Date:
2026-11-19
Location:
Manchester, UK
Years:
27
ICORE: C   QUALIS: B2   Viewed: 38677   Tracked: 16   Attend: 7

Conference Partner Index (CP-I)

61.2 / 100
Ranked #540 of 5,647 conferences · Top 10%

#30 of 336 in Data Mining & Databases

Academic recognition (35%)
68
Submission selectivity (20%) No data - scored at the neutral baseline of 50
Editions held (20%)
90
Community attention (10%)
42
Public record completeness (15%)
35

Inputs used: Listed as ICORE C, QUALIS B2 · Editions on record: 27 · Researchers following it here: 16 · Researchers who opened this page in the past 24 months: 6

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 80% - 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 2026-09-03

Call For Papers

IDEAL 2026 (International Conference on Intelligent Data Engineering and Automated Learning) is a ICORE C / QUALIS B2 conference held in Manchester, UK on 2026-11-19. The paper submission deadline is 2026-07-24 (extended). Acceptance notifications are sent on 2026-09-01.

The International Conference on Intelligent Data Engineering and Automated Learning (IDEAL) is an annual international conference dedicated to emerging and challenging topics in intelligent data analytics and associated learning systems and paradigms. Following the recent successful events: IDEAL2025 in Jaén (Spain), IDEAL2024 in Valencia (Spain), and IDEAL2023 in Évora (Portugal), the 27th edition, IDEAL2026 will be back in Manchester. Its core themes or topics include, but not limited to: Big Data Analytics Machine Learning & Deep Learning Data Mining Information Retrieval and Management Bio and Neuro-Informatics Bio-Inspired Models Agents and Hybrid Intelligent Systems Real-world Applications of Intelligent Techniques
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