acm-sigkdd-conference-on-knowledge-discovery-and-data-mining
Use when targeting ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) or deciding whether a computer-science manuscript fits this venue. Encodes conference fit, framing, evidence bar, submission-cycle checks, rebuttal posture, and desk-reject risks for data mining.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acm-sigkdd-conference-on-knowledge-discovery-and-data-mining --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) ## Conference positioning ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) is a top computer-science conference venue for data mining, applied data science, scalable learning, knowledge discovery, and impact-oriented analytics. It rewards a data-mining paper with novelty, scale, reproducibility, and clear real-world or scientific payoff. Treat this skill as a **fit / venue-selection / re-framing** tool for conference submission strategy, not as a substitute for the current year's CFP, author kit, ethics policy, or submission portal. Because CS conferences change deadlines, templates, page limits, review workflow, artifact rules, AI-use policy, and rebuttal formats every cycle, always verify the live official instructions before making a submission-ready recommendation. Start from the official source anchor recorded for this venue in `../../resources/conference-roster.md` and `../../resources/official-source-map.md`. ## When to trigger - The author names KDD / ACM SIGKDD Conference on Knowledge Discovery and Data Mining as the target venue. - A manuscript in data mining needs a conference-fit read
- Conference positioning
- When to trigger
- Scope & topic fit
- Venue-specific calibration
- Close-neighbor routing guardrail
- KDD-specific routing detail
- Method & evidence bar
- Structure & house style
- Official-cycle checklist
- Pre-submission self-check
- Common desk-reject triggers
- Re-routing decision
- Output format
What does the acm-sigkdd-conference-on-knowledge-discovery-and-data-mining skill do?
Use when targeting ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) or deciding whether a computer-science manuscript fits this venue. Encodes conference fit, framing, evidence bar, submission-cycle checks, rebuttal posture, and desk-reject risks for data mining.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acm-sigkdd-conference-on-knowledge-discovery-and-data-mining --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.