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icdm-topic-selection

Use when deciding whether a project is a strong ICDM (IEEE International Conference on Data Mining) fit, choosing among its Research, Applied, and Blue Sky tracks, and comparing ICDM with KDD, SDM, CIKM, WSDM, WWW, ICDE, or the ML flagships by contribution type, sponsor community, and the data-mining routing calendar seen from ICDM's June deadline.

ICDM-Skills/skills/icdm-topic-selection/SKILL.md

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# ICDM Topic Selection

Use this before writing. Two decisions happen here: is the work **ICDM-shaped at all**,
and if so, **which track**. ICDM is the IEEE-sponsored data-mining flagship; it rewards a
named data-mining mechanism on a defined mining task with strong baselines and a
scalability or discovery-validity story — not pure learning theory, and not a broad
deep-learning systems result.

## Fit test

- Prefer ICDM when the contribution is a **data-mining method**: pattern discovery, graph
  mining, anomaly detection, temporal/streaming mining, clustering, or scalable analytics,
  with an algorithmic idea and defensible empirical evidence.
- Route to **SDM (SIAM)** if the contribution is primarily mathematical/statistical rigor