{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:DSSMMGZ4U7FA6DWK5DT2AAJ3XS","short_pith_number":"pith:DSSMMGZ4","schema_version":"1.0","canonical_sha256":"1ca4c61b3ca7ca0f0ecae8e7a0013bbc85079300686ed73066412bfad5fb392f","source":{"kind":"arxiv","id":"1812.00125","version":1},"attestation_state":"computed","paper":{"title":"How to Profile Privacy-Conscious Users in Recommender Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CR","authors_text":"Fabrice Benhamouda, Marc Joye","submitted_at":"2018-12-01T02:16:49Z","abstract_excerpt":"Matrix factorization is a popular method to build a recommender system. In such a system, existing users and items are associated to a low-dimension vector called a profile. The profiles of a user and of an item can be combined (via inner product) to predict the rating that the user would get on the item. One important issue of such a system is the so-called cold-start problem: how to allow a user to learn her profile, so that she can then get accurate recommendations?\n  While a profile can be computed if the user is willing to rate well-chosen items and/or provide supplemental attributes or d"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1812.00125","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2018-12-01T02:16:49Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"a6a3c58878987137bd1b7a98e9d83eb2b788562e6513a8a4d7d262e9ecc44e40","abstract_canon_sha256":"885282e2b26d0867ccd5d87a1b5add2c15261f39d9de324829d7aba8172221eb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:59:27.203612Z","signature_b64":"rUCKphvP7hqjCp6s7NeTA+ZAUPm6Fv3SE6lSUz+8+NXg31tN0DGVCXknA3eu0r2fPotkCYYhvJ8QephbgLf2Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1ca4c61b3ca7ca0f0ecae8e7a0013bbc85079300686ed73066412bfad5fb392f","last_reissued_at":"2026-05-17T23:59:27.203165Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:59:27.203165Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"How to Profile Privacy-Conscious Users in Recommender Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CR","authors_text":"Fabrice Benhamouda, Marc Joye","submitted_at":"2018-12-01T02:16:49Z","abstract_excerpt":"Matrix factorization is a popular method to build a recommender system. In such a system, existing users and items are associated to a low-dimension vector called a profile. The profiles of a user and of an item can be combined (via inner product) to predict the rating that the user would get on the item. One important issue of such a system is the so-called cold-start problem: how to allow a user to learn her profile, so that she can then get accurate recommendations?\n  While a profile can be computed if the user is willing to rate well-chosen items and/or provide supplemental attributes or d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.00125","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1812.00125","created_at":"2026-05-17T23:59:27.203230+00:00"},{"alias_kind":"arxiv_version","alias_value":"1812.00125v1","created_at":"2026-05-17T23:59:27.203230+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.00125","created_at":"2026-05-17T23:59:27.203230+00:00"},{"alias_kind":"pith_short_12","alias_value":"DSSMMGZ4U7FA","created_at":"2026-05-18T12:32:19.392346+00:00"},{"alias_kind":"pith_short_16","alias_value":"DSSMMGZ4U7FA6DWK","created_at":"2026-05-18T12:32:19.392346+00:00"},{"alias_kind":"pith_short_8","alias_value":"DSSMMGZ4","created_at":"2026-05-18T12:32:19.392346+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/DSSMMGZ4U7FA6DWK5DT2AAJ3XS","json":"https://pith.science/pith/DSSMMGZ4U7FA6DWK5DT2AAJ3XS.json","graph_json":"https://pith.science/api/pith-number/DSSMMGZ4U7FA6DWK5DT2AAJ3XS/graph.json","events_json":"https://pith.science/api/pith-number/DSSMMGZ4U7FA6DWK5DT2AAJ3XS/events.json","paper":"https://pith.science/paper/DSSMMGZ4"},"agent_actions":{"view_html":"https://pith.science/pith/DSSMMGZ4U7FA6DWK5DT2AAJ3XS","download_json":"https://pith.science/pith/DSSMMGZ4U7FA6DWK5DT2AAJ3XS.json","view_paper":"https://pith.science/paper/DSSMMGZ4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1812.00125&json=true","fetch_graph":"https://pith.science/api/pith-number/DSSMMGZ4U7FA6DWK5DT2AAJ3XS/graph.json","fetch_events":"https://pith.science/api/pith-number/DSSMMGZ4U7FA6DWK5DT2AAJ3XS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DSSMMGZ4U7FA6DWK5DT2AAJ3XS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DSSMMGZ4U7FA6DWK5DT2AAJ3XS/action/storage_attestation","attest_author":"https://pith.science/pith/DSSMMGZ4U7FA6DWK5DT2AAJ3XS/action/author_attestation","sign_citation":"https://pith.science/pith/DSSMMGZ4U7FA6DWK5DT2AAJ3XS/action/citation_signature","submit_replication":"https://pith.science/pith/DSSMMGZ4U7FA6DWK5DT2AAJ3XS/action/replication_record"}},"created_at":"2026-05-17T23:59:27.203230+00:00","updated_at":"2026-05-17T23:59:27.203230+00:00"}