{"url":"/dataset/amz-computers","name":"AMZ Computers","full_name":"amazon_electronics_computers","description_markdown":"AMZ Computers is a co-purchase graph extracted from Amazon, where nodes represent products, edges represent the co-purchased relations of products, and features are bag-of-words vectors extracted from product reviews.","description_withheld":null,"homepage":"","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"Node Classification","url":"/task/node-classification","datasets_with_task":"/datasets/task/node-classification"}],"languages":[],"variants":["AMZ Computers"],"data_loaders":[],"num_papers_in_archive":9,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/node-classification-on-amz-computers","task":"Node Classification","dataset_variant":"AMZ Computers","rows":5,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"NCGCN","paper":"/paper/clarify-confused-nodes-through-separated","metrics":{"Accuracy":"90.81 ± 0.46"},"code_links":[{"title":"GISec-Team/NCGNN","url":"https://github.com/GISec-Team/NCGNN"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/clarify-confused-nodes-through-separated","title":"Clarify Confused Nodes via Separated Learning","date":"2023-06-04","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/graph-less-neural-networks-teaching-old-mlps-1","title":"Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation","date":"2021-10-17","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":8,"samples_ran":5,"samples_unverified":3,"pointer_only_for_licence":8,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/extract-the-knowledge-of-graph-neural","title":"Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework","date":"2021-03-04","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":2,"samples_unverified":1,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/towards-deeper-graph-neural-networks","title":"Towards Deeper Graph Neural Networks","date":"2020-07-18","rows_on_this_dataset":1,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":3,"samples_unverified":0,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":3,"samples_harvested":14,"samples_ran":10,"samples_unverified":4,"pointer_only_for_licence":14,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}