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About the KDD 2026 predictions

This project predicts, for each KDD 2026 attendee, who they are likely to collaborate with next, whose papers they are likely to cite, and who is likely to cite them — plus the concrete paths in the publication graph that explain each prediction.

Where the data comes from

The attendee list is derived from the authors of accepted KDD 2026 papers (DBLP), resolved to author profiles via ORCID and OpenAlex. Publication and citation history comes from OpenAlex. Everything shown is public bibliographic data.

How the predictions are made

JoinMiner represents publications, authors and venues as one heterogeneous graph. For a pair of people, it collects the paths connecting them — shared collaborators, mutual citations, co-cited papers, shared venues, and longer multi-hop chains — and a neural model scores how likely a new link between them is in the coming year. Candidate pairs are retrieved through those same path patterns, so every prediction has at least one concrete connection behind it, which is what the connection view on each page shows.

Reading the scores

Each prediction carries a 0–100 score. It is the entry's relative position among all predictions on this site — a ranking signal, not a probability. A score of 90 means the pair ranks in the top tier of what the model surfaced; it does not mean a 90% chance of collaboration. Use the ordering, not the absolute number.

Limitations

Contact

Questions, corrections, removal requests, suggestions — anything about this project goes to kdd26@joinminer.com. Updates are batched: corrections and removals appear with the next data refresh rather than immediately. For additions, include your ORCID so we can bind the right author profile; removal and correction emails sent from a profile page identify themselves.

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