Use this to audit novelty and eligibility. Reopen the current Call for Contributions for dual-submission, anonymity, and prior-publication rules before advising authors.
RecSys is a single-domain venue, but its neighbors publish recommendation-relevant work. A reviewer checks whether you cite the right neighbor, not just RecSys itself.
| Neighbor venue | What it contributes to your related work | Reviewer check |
|---|---|---|
| SIGIR | Ranking models, IR evaluation, neural retrieval | Did you distinguish recommendation from ad-hoc retrieval framing? |
| KDD | Large-scale mining, the sampled-metrics critique | Is the scalability or evaluation-methodology neighbor acknowledged? |
| WSDM / TheWebConf | Web-scale recommendation, graph and CF methods | Is the nearest web-recommendation method compared? |
| UAI | Foundational ranking (e.g., BPR) and probabilistic modeling | Are canonical recommendation methods cited to their true venue, not RecSys? |
| Reproducibility line | "Are we really making much progress?" and follow-ups | Does your evaluation answer the tuned-baseline critique head on? |
A bibliography that cites only RecSys papers tells a reviewer you may have missed the method that already solved this at a neighbor venue — a recognizable reject pattern that benchmark strength does not repair.
Imagine the paper proposes an exposure-corrected session ranker. Its nearest neighbors: a SIGIR neural ranker with no exposure correction, a KDD paper on sampled-metric bias, and a prior RecSys counterfactual-embedding paper. The novelty sentence should name all three contrasts — exposure handling where the SIGIR line ignored it, full-ranking evaluation answering the KDD critique, and a session-level objective where the prior RecSys work was static.
[Eligibility] clear / needs declaration / risky
[Closest subfields] <CF / sequential / off-policy / fairness / reproducibility>
[Nearest 3 works] <work -> distinction (with true venue)>
[Archival-overlap risk] <none / issues>
[Novelty sentence] <RecSys-ready recommendation contribution contrast>