ICDM Related Work

SkillDev tools

Use when positioning an ICDM (IEEE International Conference on Data Mining) paper's related work - lineage against prior ICDM editions and IEEE data-mining neighbors, the mechanism-contrast novelty sentence, avoiding KDD/SDM/CIKM/WSDM venue misattribution, and citing your own prior work in the third person so the section stays triple-blind-safe.

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the ICDM Related Work skill

What this skill tells your AI

The instructions your AI receives, as published by brycewang-stanford/awesome-journal-skills in ICDM-Skills/skills/icdm-related-work/SKILL.md and read by ahel’s review.

Position the paper against the data-mining literature the way an ICDM reviewer reads it: by mechanism and mining task, not by benchmark leaderboard. The section has two ICDM constraints — it must contrast your mechanism with prior mechanisms, and it must do so without breaking the Research Track's triple-blind anonymity or misattributing sibling-venue work to ICDM.

Position by mechanism, not by results table

  • For each closely related method, state what mechanism it uses and the specific thing your mechanism changes: the isolation criterion, the sparsity structure, the walk kernel, the sketch, the update rule. "We also do anomaly detection" is not positioning.
  • Group prior work by the mining primitive it shares with you, so the reader sees the lineage your contribution extends or breaks.
  • End the closest-competitor paragraph with a one-sentence mechanism-contrast: "Unlike [X], which stores the full graph to compute isolation depth, our sketch estimates it in one pass with a stated error." That sentence is the novelty claim reviewers quote.

Cite the ICDM lineage where it exists

ICDM has durable research lines you can anchor to — random walks with restart, isolation-based detection, sparse linear recommendation, scalable graph systems, corrected time-series averaging (see resources/exemplars/library.md). Situating your work in an ICDM line signals venue fit. But cite the paper for its mechanism, and verify the edition on dblp before attributing anything.

The misattribution trap

Data-mining fame does not mean ICDM placement. Getting a venue wrong in related work is a credibility hit a data-mining reviewer notices immediately.

Paper / methodActual venueNot
node2vec, DeepWalkKDDICDM
LINE (network embedding)WWWICDM
SMOTEJAIR (journal)ICDM
t-SNE, Kernel Two-Sample TestJMLR (journal)ICDM
Many "SDM" mining papersSDM (SIAM)ICDM

Check each citation's venue on dblp; ICDM, KDD, CIKM, WSDM, and SDM overlap in topic and are easy to confuse.

Keep it triple-blind-safe

  • Cite your own prior work in the third person: "Building on the sketch of [12]," not "building on our sketch of [12]."
  • Do not signal a research program only your group could have ("in our line of work on X").
  • Do not cite an anonymized-breaking preprint by a title that de-anonymizes you; if a concurrent arXiv version exists, follow the current call's policy on declaring it.

Handle concurrent and recent work

  • ICDM's June deadline sits after the spring conference season; recent CIKM, WWW, and KDD cycles may contain concurrent work. Acknowledge genuinely concurrent results as concurrent, not as prior art you failed to beat.
  • Because the whole section lives inside the 10-page all-inclusive cap, prune citations that do not sharpen the mechanism contrast; a padded related-work section costs you body space.

Vignette: a novelty sentence that survived review

An author's first draft said "our method is related to random-walk methods and embedding methods." The revision named the closest competitor's mechanism (full-graph restart computation), stated the delta (single-pass estimation with a bound), verified on dblp that the competitor was an ICDM paper and that a wrongly-cited "ICDM" embedding paper was actually a KDD paper, and rewrote the self-citation in the third person. The section shrank by a third and the novelty claim became a single quotable sentence.

Output format

[Positioning] mechanism-contrast / results-only (fix if results-only)
[Novelty sentence] <one-sentence mechanism delta vs closest work>
[Venue check] all citations verified on dblp: yes / misattributions found
[Anonymity] third-person self-cites: yes / leaks found
[Trim list] <citations to cut to protect the 10-page cap>

Signals

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skill
Key
icdm-related-work
Source
github.com/brycewang-stanford/awesome-journal-skills