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Data miningCORE A* · CCF A

SIGKDD 2027 deadline

ACM Knowledge Discovery and Data Mining
August 1-5, 2027 · San Jose, California, USA

Official call for papers

All deadlines for this edition have passed.

Key dates

  1. Abstract / registration

    Sun, Jul 19, 2026 · 23:59 AoE

  2. Full paper

    Sun, Jul 26, 2026 · 23:59 AoE

  3. Author response ends

    Tue, Oct 13, 2026 · 23:59 AoE

  4. Decisions

    Sat, Nov 14, 2026 · 23:59 AoE

    1st round of 2 total rounds

  5. Conference

    August 1-5, 2027 · San Jose, California, USA

What SIGKDD reviewers will look for

KDD 2026 runs two cycles (Feb and Aug) on OpenReview with at least three reviews per paper, overseen by ACs and SACs. Reviewers write a summary, numbered strengths and weaknesses, check whether a resubmission addressed earlier reviews, pose rebuttal questions, and rate Relevance, Novelty, Technical Quality, Presentation and Reproducibility on 1–4 (High / Moderate / Low) plus confidence. ACs weigh technical merit, originality, potential impact, execution, presentation, related work, reproducibility and ethics. February submissions can receive a Resubmit decision for the next cycle.

Overall score
Technical Quality, 1–4 (top: “High - The paper exhibits a high level of technical quality with a rigorous and well-executed methodology and analysis. The results are highly reliable, well-supported, and thorough. The work demonstrates technical excellence and sets a high standard for quality in the field.”)
Sub-scores
Relevance, Novelty, Presentation, Reproducibility (1–4)
Written fields
Paper Summary · Paper Strengths · Paper Weaknesses · Resubmission · Questions And Suggestions For Rebuttal · Ethics Review Flag · Ethics Review Description
Author checklist
KDD submission requirements, 4 items

Where the bar sits. KDD 2026 Cycle 1 accepted 256 of 1,215 research-track papers (21%; KDD 2025: 18.7%). KDD has no overall score visible to authors; Novelty and Technical Quality act as the headline ratings. Shared averages of accepted papers cluster around 3 (Moderate) on each 1–4 axis, so a Technical Quality mean ≥ 3 with Novelty ≥ 3 is competitive and ~2.6–3 borderline.

LLM policy for reviewers

KDD 2026 requires any use of generative AI during reviewing to be disclosed in the review form, and forbids uploading any passage of a paper under review to a generative AI tool.

Official policy
The full KDD review form, field by field

Deadline data from ccf-deadlines (MIT license), refreshed every 6 hours. We check the headline venues against their official calls for papers where we can, but deadlines move: always confirm on the official site before you plan around a date. “Estimated” dates are projected from the previous edition and are not announcements.

Times are shown in AoE (Anywhere on Earth, UTC−12) and in your local timezone. Spot an error? Report it upstream so everyone gets the fix.