{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:FZR767LEOG2NG2ISH35CSYV5XN","short_pith_number":"pith:FZR767LE","canonical_record":{"source":{"id":"1901.04704","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-15T08:25:00Z","cross_cats_sorted":["cs.IR","stat.ML"],"title_canon_sha256":"513aa6f3b17f5cd7d0fac63ecf865d56e6637e1ee8214ac56ba2b62af465d77e","abstract_canon_sha256":"976bb42d11dc43ec7e9681f7cc1301e7c4adb4fe21b0a071d508351f33e37b8a"},"schema_version":"1.0"},"canonical_sha256":"2e63ff7d6471b4d369123efa2962bdbb6aa729e874f4dccdfe52d45859e9cbc9","source":{"kind":"arxiv","id":"1901.04704","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.04704","created_at":"2026-05-17T23:56:22Z"},{"alias_kind":"arxiv_version","alias_value":"1901.04704v1","created_at":"2026-05-17T23:56:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.04704","created_at":"2026-05-17T23:56:22Z"},{"alias_kind":"pith_short_12","alias_value":"FZR767LEOG2N","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_16","alias_value":"FZR767LEOG2NG2IS","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_8","alias_value":"FZR767LE","created_at":"2026-05-18T12:33:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:FZR767LEOG2NG2ISH35CSYV5XN","target":"record","payload":{"canonical_record":{"source":{"id":"1901.04704","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-15T08:25:00Z","cross_cats_sorted":["cs.IR","stat.ML"],"title_canon_sha256":"513aa6f3b17f5cd7d0fac63ecf865d56e6637e1ee8214ac56ba2b62af465d77e","abstract_canon_sha256":"976bb42d11dc43ec7e9681f7cc1301e7c4adb4fe21b0a071d508351f33e37b8a"},"schema_version":"1.0"},"canonical_sha256":"2e63ff7d6471b4d369123efa2962bdbb6aa729e874f4dccdfe52d45859e9cbc9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:56:22.001153Z","signature_b64":"KKh15ey+GmmfZy7MDeCInxW4de0zf3oKwPtQJSE2nUt20wIQj/mIcMCZbi30v872l7aYsZtGwnsJ2Q28gXRgBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2e63ff7d6471b4d369123efa2962bdbb6aa729e874f4dccdfe52d45859e9cbc9","last_reissued_at":"2026-05-17T23:56:22.000570Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:56:22.000570Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1901.04704","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:56:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xkvOdsk3RMAwTYSRlFtpaoueetEx+seMxaw4J7HCg9CSVl3Ubo43KCTFmX2HWTYxTcYgCL/OB+qUJPrrOpJLBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T21:55:18.368108Z"},"content_sha256":"a86e0f21602895071fe2c615ee0977e228503c5d1644d116c79e92102fe35a53","schema_version":"1.0","event_id":"sha256:a86e0f21602895071fe2c615ee0977e228503c5d1644d116c79e92102fe35a53"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:FZR767LEOG2NG2ISH35CSYV5XN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR","stat.ML"],"primary_cat":"cs.LG","authors_text":"Chang-Dong Wang, Jian-Huang Lai, Ling Huang, Philip S. Yu, Zhi-Hong Deng","submitted_at":"2019-01-15T08:25:00Z","abstract_excerpt":"In general, recommendation can be viewed as a matching problem, i.e., match proper items for proper users. However, due to the huge semantic gap between users and items, it's almost impossible to directly match users and items in their initial representation spaces. To solve this problem, many methods have been studied, which can be generally categorized into two types, i.e., representation learning-based CF methods and matching function learning-based CF methods. Representation learning-based CF methods try to map users and items into a common representation space. In this case, the higher si"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.04704","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:56:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kNSbWB+vBUb5Yi4szYXfpUDj5zs0f+TJVrqRX+0pibZyL6XueFaC0bCJu+wFAq/4NgvahonP+oDQ0O5LVv1GAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T21:55:18.368812Z"},"content_sha256":"1b0fb48ef945cdf5d287c4a3d29534e5c375db3171774d8a8c2972d4efd7f638","schema_version":"1.0","event_id":"sha256:1b0fb48ef945cdf5d287c4a3d29534e5c375db3171774d8a8c2972d4efd7f638"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FZR767LEOG2NG2ISH35CSYV5XN/bundle.json","state_url":"https://pith.science/pith/FZR767LEOG2NG2ISH35CSYV5XN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FZR767LEOG2NG2ISH35CSYV5XN/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-09T21:55:18Z","links":{"resolver":"https://pith.science/pith/FZR767LEOG2NG2ISH35CSYV5XN","bundle":"https://pith.science/pith/FZR767LEOG2NG2ISH35CSYV5XN/bundle.json","state":"https://pith.science/pith/FZR767LEOG2NG2ISH35CSYV5XN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FZR767LEOG2NG2ISH35CSYV5XN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:FZR767LEOG2NG2ISH35CSYV5XN","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"976bb42d11dc43ec7e9681f7cc1301e7c4adb4fe21b0a071d508351f33e37b8a","cross_cats_sorted":["cs.IR","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-15T08:25:00Z","title_canon_sha256":"513aa6f3b17f5cd7d0fac63ecf865d56e6637e1ee8214ac56ba2b62af465d77e"},"schema_version":"1.0","source":{"id":"1901.04704","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.04704","created_at":"2026-05-17T23:56:22Z"},{"alias_kind":"arxiv_version","alias_value":"1901.04704v1","created_at":"2026-05-17T23:56:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.04704","created_at":"2026-05-17T23:56:22Z"},{"alias_kind":"pith_short_12","alias_value":"FZR767LEOG2N","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_16","alias_value":"FZR767LEOG2NG2IS","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_8","alias_value":"FZR767LE","created_at":"2026-05-18T12:33:18Z"}],"graph_snapshots":[{"event_id":"sha256:1b0fb48ef945cdf5d287c4a3d29534e5c375db3171774d8a8c2972d4efd7f638","target":"graph","created_at":"2026-05-17T23:56:22Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"In general, recommendation can be viewed as a matching problem, i.e., match proper items for proper users. However, due to the huge semantic gap between users and items, it's almost impossible to directly match users and items in their initial representation spaces. To solve this problem, many methods have been studied, which can be generally categorized into two types, i.e., representation learning-based CF methods and matching function learning-based CF methods. Representation learning-based CF methods try to map users and items into a common representation space. In this case, the higher si","authors_text":"Chang-Dong Wang, Jian-Huang Lai, Ling Huang, Philip S. Yu, Zhi-Hong Deng","cross_cats":["cs.IR","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-15T08:25:00Z","title":"DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.04704","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:a86e0f21602895071fe2c615ee0977e228503c5d1644d116c79e92102fe35a53","target":"record","created_at":"2026-05-17T23:56:22Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"976bb42d11dc43ec7e9681f7cc1301e7c4adb4fe21b0a071d508351f33e37b8a","cross_cats_sorted":["cs.IR","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-15T08:25:00Z","title_canon_sha256":"513aa6f3b17f5cd7d0fac63ecf865d56e6637e1ee8214ac56ba2b62af465d77e"},"schema_version":"1.0","source":{"id":"1901.04704","kind":"arxiv","version":1}},"canonical_sha256":"2e63ff7d6471b4d369123efa2962bdbb6aa729e874f4dccdfe52d45859e9cbc9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2e63ff7d6471b4d369123efa2962bdbb6aa729e874f4dccdfe52d45859e9cbc9","first_computed_at":"2026-05-17T23:56:22.000570Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:56:22.000570Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KKh15ey+GmmfZy7MDeCInxW4de0zf3oKwPtQJSE2nUt20wIQj/mIcMCZbi30v872l7aYsZtGwnsJ2Q28gXRgBg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:56:22.001153Z","signed_message":"canonical_sha256_bytes"},"source_id":"1901.04704","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a86e0f21602895071fe2c615ee0977e228503c5d1644d116c79e92102fe35a53","sha256:1b0fb48ef945cdf5d287c4a3d29534e5c375db3171774d8a8c2972d4efd7f638"],"state_sha256":"393e95e707e672e6636c32e825b6be8a41edf5e81a665ccc129c722caf31febb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TOpdglp0yRPeFZqM37XZA7JQnnq7PvUyjWe7m8GHRGBG4Nf/c4r0fKDnoPLEs1UaGViZlKr80z+RnxLLZmiEAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-09T21:55:18.372738Z","bundle_sha256":"cba337420f2111963678f3542d0888d41cfcde3abe977729cb804c0b89c9f058"}}