{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:T5ATE6IKUUTDP4GY4436HQOY4M","short_pith_number":"pith:T5ATE6IK","canonical_record":{"source":{"id":"2207.13262","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2022-07-27T02:56:10Z","cross_cats_sorted":[],"title_canon_sha256":"2c6ead1cc9119a41c284336ad522f7a92e1801e13f938c88204d5cf5c91eafee","abstract_canon_sha256":"81319b90b32b5d437ca908d9e3dc45b9abf7f3286a5cb4e23948a9618f1d9798"},"schema_version":"1.0"},"canonical_sha256":"9f4132790aa52637f0d8e737e3c1d8e315075bd96b8ad84102e0dad5521110f7","source":{"kind":"arxiv","id":"2207.13262","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.13262","created_at":"2026-07-05T04:44:04Z"},{"alias_kind":"arxiv_version","alias_value":"2207.13262v1","created_at":"2026-07-05T04:44:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.13262","created_at":"2026-07-05T04:44:04Z"},{"alias_kind":"pith_short_12","alias_value":"T5ATE6IKUUTD","created_at":"2026-07-05T04:44:04Z"},{"alias_kind":"pith_short_16","alias_value":"T5ATE6IKUUTDP4GY","created_at":"2026-07-05T04:44:04Z"},{"alias_kind":"pith_short_8","alias_value":"T5ATE6IK","created_at":"2026-07-05T04:44:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:T5ATE6IKUUTDP4GY4436HQOY4M","target":"record","payload":{"canonical_record":{"source":{"id":"2207.13262","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2022-07-27T02:56:10Z","cross_cats_sorted":[],"title_canon_sha256":"2c6ead1cc9119a41c284336ad522f7a92e1801e13f938c88204d5cf5c91eafee","abstract_canon_sha256":"81319b90b32b5d437ca908d9e3dc45b9abf7f3286a5cb4e23948a9618f1d9798"},"schema_version":"1.0"},"canonical_sha256":"9f4132790aa52637f0d8e737e3c1d8e315075bd96b8ad84102e0dad5521110f7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:44:04.759238Z","signature_b64":"2AEyzpp5xpzQq5x60+r9LmvkqjFyeMcRLTElvqeDzUyD00vsxZ6JO+UdW+wXzji1bGPG+DpD4Kn/T1cxMwBlAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9f4132790aa52637f0d8e737e3c1d8e315075bd96b8ad84102e0dad5521110f7","last_reissued_at":"2026-07-05T04:44:04.758836Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:44:04.758836Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2207.13262","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":"2026-07-05T04:44:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yBoAp28n8aM9193zOFSIAPtNiRpmVnYMQBdY6JcTjOv0UW4njaVErS72sR7ItpNrbQwEEJSqwRd/oWkZq8t/Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T11:15:41.125174Z"},"content_sha256":"20f3abc38aa511d7bd2b235ace9773b96596a41849ed68eb75b0834fa80e9e4c","schema_version":"1.0","event_id":"sha256:20f3abc38aa511d7bd2b235ace9773b96596a41849ed68eb75b0834fa80e9e4c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:T5ATE6IKUUTDP4GY4436HQOY4M","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Factorial User Modeling with Hierarchical Graph Neural Network for Enhanced Sequential Recommendation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Deqing Yang, Lyuxin Xue, Yanghua Xiao","submitted_at":"2022-07-27T02:56:10Z","abstract_excerpt":"Most sequential recommendation (SR) systems employing graph neural networks (GNNs) only model a user's interaction sequence as a flat graph without hierarchy, overlooking diverse factors in the user's preference. Moreover, the timespan between interacted items is not sufficiently utilized by previous models, restricting SR performance gains. To address these problems, we propose a novel SR system employing a hierarchical graph neural network (HGNN) to model factorial user preferences. Specifically, a timespan-aware sequence graph (TSG) for the target user is first constructed with the timespan"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.13262","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2207.13262/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":"2026-07-05T04:44:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"A6Rd12hd153Ruoc81J/rm+zDeYZ3xFXFuaJEBjLFeBkAsJHhqmuIvtra+nzrPXBeq7CTZzdPd3SkMvFNfB4wDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T11:15:41.125665Z"},"content_sha256":"717f5dea5e39d2c28eaa36397461e428f082fcf37f9e4d239bb3d023197c2b8d","schema_version":"1.0","event_id":"sha256:717f5dea5e39d2c28eaa36397461e428f082fcf37f9e4d239bb3d023197c2b8d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/T5ATE6IKUUTDP4GY4436HQOY4M/bundle.json","state_url":"https://pith.science/pith/T5ATE6IKUUTDP4GY4436HQOY4M/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/T5ATE6IKUUTDP4GY4436HQOY4M/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":"2026-08-22T11:15:41Z","links":{"resolver":"https://pith.science/pith/T5ATE6IKUUTDP4GY4436HQOY4M","bundle":"https://pith.science/pith/T5ATE6IKUUTDP4GY4436HQOY4M/bundle.json","state":"https://pith.science/pith/T5ATE6IKUUTDP4GY4436HQOY4M/state.json","well_known_bundle":"https://pith.science/.well-known/pith/T5ATE6IKUUTDP4GY4436HQOY4M/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:T5ATE6IKUUTDP4GY4436HQOY4M","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":"81319b90b32b5d437ca908d9e3dc45b9abf7f3286a5cb4e23948a9618f1d9798","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2022-07-27T02:56:10Z","title_canon_sha256":"2c6ead1cc9119a41c284336ad522f7a92e1801e13f938c88204d5cf5c91eafee"},"schema_version":"1.0","source":{"id":"2207.13262","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.13262","created_at":"2026-07-05T04:44:04Z"},{"alias_kind":"arxiv_version","alias_value":"2207.13262v1","created_at":"2026-07-05T04:44:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.13262","created_at":"2026-07-05T04:44:04Z"},{"alias_kind":"pith_short_12","alias_value":"T5ATE6IKUUTD","created_at":"2026-07-05T04:44:04Z"},{"alias_kind":"pith_short_16","alias_value":"T5ATE6IKUUTDP4GY","created_at":"2026-07-05T04:44:04Z"},{"alias_kind":"pith_short_8","alias_value":"T5ATE6IK","created_at":"2026-07-05T04:44:04Z"}],"graph_snapshots":[{"event_id":"sha256:717f5dea5e39d2c28eaa36397461e428f082fcf37f9e4d239bb3d023197c2b8d","target":"graph","created_at":"2026-07-05T04:44:04Z","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/2207.13262/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Most sequential recommendation (SR) systems employing graph neural networks (GNNs) only model a user's interaction sequence as a flat graph without hierarchy, overlooking diverse factors in the user's preference. Moreover, the timespan between interacted items is not sufficiently utilized by previous models, restricting SR performance gains. To address these problems, we propose a novel SR system employing a hierarchical graph neural network (HGNN) to model factorial user preferences. Specifically, a timespan-aware sequence graph (TSG) for the target user is first constructed with the timespan","authors_text":"Deqing Yang, Lyuxin Xue, Yanghua Xiao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2022-07-27T02:56:10Z","title":"Factorial User Modeling with Hierarchical Graph Neural Network for Enhanced Sequential Recommendation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.13262","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":"sha256:20f3abc38aa511d7bd2b235ace9773b96596a41849ed68eb75b0834fa80e9e4c","target":"record","created_at":"2026-07-05T04:44:04Z","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":"81319b90b32b5d437ca908d9e3dc45b9abf7f3286a5cb4e23948a9618f1d9798","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2022-07-27T02:56:10Z","title_canon_sha256":"2c6ead1cc9119a41c284336ad522f7a92e1801e13f938c88204d5cf5c91eafee"},"schema_version":"1.0","source":{"id":"2207.13262","kind":"arxiv","version":1}},"canonical_sha256":"9f4132790aa52637f0d8e737e3c1d8e315075bd96b8ad84102e0dad5521110f7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9f4132790aa52637f0d8e737e3c1d8e315075bd96b8ad84102e0dad5521110f7","first_computed_at":"2026-07-05T04:44:04.758836Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:44:04.758836Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2AEyzpp5xpzQq5x60+r9LmvkqjFyeMcRLTElvqeDzUyD00vsxZ6JO+UdW+wXzji1bGPG+DpD4Kn/T1cxMwBlAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:44:04.759238Z","signed_message":"canonical_sha256_bytes"},"source_id":"2207.13262","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:20f3abc38aa511d7bd2b235ace9773b96596a41849ed68eb75b0834fa80e9e4c","sha256:717f5dea5e39d2c28eaa36397461e428f082fcf37f9e4d239bb3d023197c2b8d"],"state_sha256":"fd23481458fa51efc38bd4e5dab3084704d8926a3a00e26dae5234de01193e98"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nNXwOULXelysB9gf9RjobLlioMRww5+acrlpkWCh9u441K7/XATCVRRSykad247+tgMBoHD5GvIamMZfYIKVAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T11:15:41.130328Z","bundle_sha256":"5fb9412b161d1c75126d0d21aa19401ab2e03364b65a9e6f83f4c662ceaa17ef"}}