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kdd-topic-selection

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Use when deciding whether a project belongs at KDD and in which track — Research vs Applied Data Science vs Datasets and Benchmarks vs AI for Sciences — or whether it routes to ICDM, SDM, WSDM, CIKM, WWW, VLDB, or an ML flagship. Covers the deployment-evidence fork, data-regime framing, and SIGKDD fit signals before writing.

When to use

• deciding if a project is KDD-shaped
• selecting KDD track (Research, ADS, Datasets, AI for Sciences)
• routing to neighbor venues (ICDM, SDM, WSDM, CIKM, WWW, VLDB, ML flagships)
• evaluating deployment-evidence fork
• framing data-regime signals
• checking SIGKDD fit signals

When not to use

• writing the paper
• reviewing KDD submissions
• managing KDD workflow timelines

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