{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:EYPGK7COUJKXARXGFYMTOSJRHR","short_pith_number":"pith:EYPGK7CO","canonical_record":{"source":{"id":"1905.13130","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2019-05-27T08:27:36Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"56ded9efe16d106bb3fb2b6b4dba12e9210cf9d9ed6f6890b2c12186834f4fbb","abstract_canon_sha256":"accdc1476e4827b190f61c9024ef421754eaf8c34f3146bb13cadfb159d69a31"},"schema_version":"1.0"},"canonical_sha256":"261e657c4ea2557046e62e193749313c733d25e153e1b2e5f45b60e445493c61","source":{"kind":"arxiv","id":"1905.13130","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.13130","created_at":"2026-07-05T00:17:27Z"},{"alias_kind":"arxiv_version","alias_value":"1905.13130v2","created_at":"2026-07-05T00:17:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.13130","created_at":"2026-07-05T00:17:27Z"},{"alias_kind":"pith_short_12","alias_value":"EYPGK7COUJKX","created_at":"2026-07-05T00:17:27Z"},{"alias_kind":"pith_short_16","alias_value":"EYPGK7COUJKXARXG","created_at":"2026-07-05T00:17:27Z"},{"alias_kind":"pith_short_8","alias_value":"EYPGK7CO","created_at":"2026-07-05T00:17:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:EYPGK7COUJKXARXGFYMTOSJRHR","target":"record","payload":{"canonical_record":{"source":{"id":"1905.13130","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2019-05-27T08:27:36Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"56ded9efe16d106bb3fb2b6b4dba12e9210cf9d9ed6f6890b2c12186834f4fbb","abstract_canon_sha256":"accdc1476e4827b190f61c9024ef421754eaf8c34f3146bb13cadfb159d69a31"},"schema_version":"1.0"},"canonical_sha256":"261e657c4ea2557046e62e193749313c733d25e153e1b2e5f45b60e445493c61","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:17:27.136522Z","signature_b64":"XhmTykeHbY0t55Tw3xMLmU/r73T2PKcNeC1kr1QQkVaRR2oUyTq2WFwH5jgZ8ZFPDbbygA6FF/tcbR5kvXe5BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"261e657c4ea2557046e62e193749313c733d25e153e1b2e5f45b60e445493c61","last_reissued_at":"2026-07-05T00:17:27.136090Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:17:27.136090Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1905.13130","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:17:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"r3f0Wkt0+c4nrF41fc70ebUhD0PjBznCRtcx8S0EXPDt+vypguv8U2Zdw+gG38t2Y9APBSoVcRsjL0dhr0UbAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-10T16:46:01.416370Z"},"content_sha256":"c584da628ecf2585cb50d048640c46da7dc3728740b2d7a0a6072ceeede79b40","schema_version":"1.0","event_id":"sha256:c584da628ecf2585cb50d048640c46da7dc3728740b2d7a0a6072ceeede79b40"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:EYPGK7COUJKXARXGFYMTOSJRHR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SAIN: Self-Attentive Integration Network for Recommendation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.IR","authors_text":"Jaewoo Kang, Miyoung Ko, Raehyun Kim, Seoungjun Yun","submitted_at":"2019-05-27T08:27:36Z","abstract_excerpt":"With the growing importance of personalized recommendation, numerous recommendation models have been proposed recently. Among them, Matrix Factorization (MF) based models are the most widely used in the recommendation field due to their high performance. However, MF based models suffer from cold start problems where user-item interactions are sparse. To deal with this problem, content based recommendation models which use the auxiliary attributes of users and items have been proposed. Since these models use auxiliary attributes, they are effective in cold start settings. However, most of the p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.13130","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1905.13130/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T00:17:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MoJyi56A2uhj0QETABaPs8q5V5UgSLdZmm1KrIm2ilZRHbbOo4qJ8tjg67an6KmKXw2E5sgd/WBIqJCBBDGEAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-10T16:46:01.416754Z"},"content_sha256":"db01771533bbf15ca7de2643db47c02274b9446c9e82f63a9a40cd04c2d58145","schema_version":"1.0","event_id":"sha256:db01771533bbf15ca7de2643db47c02274b9446c9e82f63a9a40cd04c2d58145"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EYPGK7COUJKXARXGFYMTOSJRHR/bundle.json","state_url":"https://pith.science/pith/EYPGK7COUJKXARXGFYMTOSJRHR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EYPGK7COUJKXARXGFYMTOSJRHR/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":"2026-07-10T16:46:01Z","links":{"resolver":"https://pith.science/pith/EYPGK7COUJKXARXGFYMTOSJRHR","bundle":"https://pith.science/pith/EYPGK7COUJKXARXGFYMTOSJRHR/bundle.json","state":"https://pith.science/pith/EYPGK7COUJKXARXGFYMTOSJRHR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EYPGK7COUJKXARXGFYMTOSJRHR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:EYPGK7COUJKXARXGFYMTOSJRHR","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":"accdc1476e4827b190f61c9024ef421754eaf8c34f3146bb13cadfb159d69a31","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2019-05-27T08:27:36Z","title_canon_sha256":"56ded9efe16d106bb3fb2b6b4dba12e9210cf9d9ed6f6890b2c12186834f4fbb"},"schema_version":"1.0","source":{"id":"1905.13130","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.13130","created_at":"2026-07-05T00:17:27Z"},{"alias_kind":"arxiv_version","alias_value":"1905.13130v2","created_at":"2026-07-05T00:17:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.13130","created_at":"2026-07-05T00:17:27Z"},{"alias_kind":"pith_short_12","alias_value":"EYPGK7COUJKX","created_at":"2026-07-05T00:17:27Z"},{"alias_kind":"pith_short_16","alias_value":"EYPGK7COUJKXARXG","created_at":"2026-07-05T00:17:27Z"},{"alias_kind":"pith_short_8","alias_value":"EYPGK7CO","created_at":"2026-07-05T00:17:27Z"}],"graph_snapshots":[{"event_id":"sha256:db01771533bbf15ca7de2643db47c02274b9446c9e82f63a9a40cd04c2d58145","target":"graph","created_at":"2026-07-05T00:17:27Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1905.13130/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the growing importance of personalized recommendation, numerous recommendation models have been proposed recently. Among them, Matrix Factorization (MF) based models are the most widely used in the recommendation field due to their high performance. However, MF based models suffer from cold start problems where user-item interactions are sparse. To deal with this problem, content based recommendation models which use the auxiliary attributes of users and items have been proposed. Since these models use auxiliary attributes, they are effective in cold start settings. However, most of the p","authors_text":"Jaewoo Kang, Miyoung Ko, Raehyun Kim, Seoungjun Yun","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2019-05-27T08:27:36Z","title":"SAIN: Self-Attentive Integration Network for Recommendation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.13130","kind":"arxiv","version":2},"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:c584da628ecf2585cb50d048640c46da7dc3728740b2d7a0a6072ceeede79b40","target":"record","created_at":"2026-07-05T00:17:27Z","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":"accdc1476e4827b190f61c9024ef421754eaf8c34f3146bb13cadfb159d69a31","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2019-05-27T08:27:36Z","title_canon_sha256":"56ded9efe16d106bb3fb2b6b4dba12e9210cf9d9ed6f6890b2c12186834f4fbb"},"schema_version":"1.0","source":{"id":"1905.13130","kind":"arxiv","version":2}},"canonical_sha256":"261e657c4ea2557046e62e193749313c733d25e153e1b2e5f45b60e445493c61","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"261e657c4ea2557046e62e193749313c733d25e153e1b2e5f45b60e445493c61","first_computed_at":"2026-07-05T00:17:27.136090Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:17:27.136090Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XhmTykeHbY0t55Tw3xMLmU/r73T2PKcNeC1kr1QQkVaRR2oUyTq2WFwH5jgZ8ZFPDbbygA6FF/tcbR5kvXe5BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T00:17:27.136522Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.13130","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c584da628ecf2585cb50d048640c46da7dc3728740b2d7a0a6072ceeede79b40","sha256:db01771533bbf15ca7de2643db47c02274b9446c9e82f63a9a40cd04c2d58145"],"state_sha256":"c2634fa182c0f576ae39aa0e03685dde01f47a4efe0e4e399a50b15ff204d3d0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nK8cHPUw+A7PWn0FhZn/ivnxQMHWJxpEIU8KZTRn398WBfMmcgLS5USuqKCFOX6cY9Ssvix2WOyfb2JfM5krBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-10T16:46:01.419213Z","bundle_sha256":"6adba0060b1c4bd5b20367dd73cf20f0c1e9d5c3a6fe01b32deeb813db57deb5"}}