{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:76CBTVULSR5DC2SC6ZRUSJ4ROY","short_pith_number":"pith:76CBTVUL","canonical_record":{"source":{"id":"2311.13277","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2023-11-22T09:53:57Z","cross_cats_sorted":[],"title_canon_sha256":"badb18f2a6a09dcf41a3ade6edee2f1f0c9d5c693d37a5d5c6cf0658ed3d4807","abstract_canon_sha256":"e11b8998bcb2dca7b213e04b8b44e0dc94707658dbb8600c74c94fbe51b23052"},"schema_version":"1.0"},"canonical_sha256":"ff8419d68b947a316a42f663492791762fe2859ada3aa96802fc786702d3653f","source":{"kind":"arxiv","id":"2311.13277","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.13277","created_at":"2026-07-05T07:53:32Z"},{"alias_kind":"arxiv_version","alias_value":"2311.13277v2","created_at":"2026-07-05T07:53:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.13277","created_at":"2026-07-05T07:53:32Z"},{"alias_kind":"pith_short_12","alias_value":"76CBTVULSR5D","created_at":"2026-07-05T07:53:32Z"},{"alias_kind":"pith_short_16","alias_value":"76CBTVULSR5DC2SC","created_at":"2026-07-05T07:53:32Z"},{"alias_kind":"pith_short_8","alias_value":"76CBTVUL","created_at":"2026-07-05T07:53:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:76CBTVULSR5DC2SC6ZRUSJ4ROY","target":"record","payload":{"canonical_record":{"source":{"id":"2311.13277","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2023-11-22T09:53:57Z","cross_cats_sorted":[],"title_canon_sha256":"badb18f2a6a09dcf41a3ade6edee2f1f0c9d5c693d37a5d5c6cf0658ed3d4807","abstract_canon_sha256":"e11b8998bcb2dca7b213e04b8b44e0dc94707658dbb8600c74c94fbe51b23052"},"schema_version":"1.0"},"canonical_sha256":"ff8419d68b947a316a42f663492791762fe2859ada3aa96802fc786702d3653f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:53:32.097770Z","signature_b64":"t9IkuiGD9Fh1CIL4ddhklGsxfJQzU3ACe1Mq+bGTdQodAcHurEJde2nlf5iD5AOuODz/WQwc8iTXxd27KrV3BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ff8419d68b947a316a42f663492791762fe2859ada3aa96802fc786702d3653f","last_reissued_at":"2026-07-05T07:53:32.097340Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:53:32.097340Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.13277","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":"2026-07-05T07:53:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4Sw+CVbWtxDy29LSOkUvIbkx44obbM1+knz2ru5fTQuKimkZRQmx5XnqvO9Cq7qBZ/AfaDSWno10OxdRnCbMAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T17:29:07.423090Z"},"content_sha256":"f39fcc5be5efa72c4210f6e74517406e4c1315e287a6274659c2edefa7cb8290","schema_version":"1.0","event_id":"sha256:f39fcc5be5efa72c4210f6e74517406e4c1315e287a6274659c2edefa7cb8290"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:76CBTVULSR5DC2SC6ZRUSJ4ROY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Hierarchical Matrix Factorization for Interpretable Collaborative Filtering","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Kai Sugahara, Kazushi Okamoto","submitted_at":"2023-11-22T09:53:57Z","abstract_excerpt":"Matrix factorization (MF) is a simple collaborative filtering technique that achieves superior recommendation accuracy by decomposing the user-item interaction matrix into user and item latent matrices. Because the model typically learns each interaction independently, it may overlook the underlying shared dependencies between users and items, resulting in less stable and interpretable recommendations. Based on these insights, we propose \"Hierarchical Matrix Factorization\" (HMF), which incorporates clustering concepts to capture the hierarchy, where leaf nodes and other nodes correspond to use"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.13277","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/2311.13277/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":"2026-07-05T07:53:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OTaLUNYxLTNIhPgSiV2PKTiALYWNUz/nKnJfoE+W/8dxd+iOdW67d/dJcp7n0cWylmLI3aOsCMuKMecc6NrqBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T17:29:07.423607Z"},"content_sha256":"0e2f6531df82bfcdf9d6f3bf221a9bfd91e7d6f34264a144171b3894c386feb2","schema_version":"1.0","event_id":"sha256:0e2f6531df82bfcdf9d6f3bf221a9bfd91e7d6f34264a144171b3894c386feb2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/76CBTVULSR5DC2SC6ZRUSJ4ROY/bundle.json","state_url":"https://pith.science/pith/76CBTVULSR5DC2SC6ZRUSJ4ROY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/76CBTVULSR5DC2SC6ZRUSJ4ROY/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":"2026-08-15T17:29:07Z","links":{"resolver":"https://pith.science/pith/76CBTVULSR5DC2SC6ZRUSJ4ROY","bundle":"https://pith.science/pith/76CBTVULSR5DC2SC6ZRUSJ4ROY/bundle.json","state":"https://pith.science/pith/76CBTVULSR5DC2SC6ZRUSJ4ROY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/76CBTVULSR5DC2SC6ZRUSJ4ROY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:76CBTVULSR5DC2SC6ZRUSJ4ROY","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":"e11b8998bcb2dca7b213e04b8b44e0dc94707658dbb8600c74c94fbe51b23052","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2023-11-22T09:53:57Z","title_canon_sha256":"badb18f2a6a09dcf41a3ade6edee2f1f0c9d5c693d37a5d5c6cf0658ed3d4807"},"schema_version":"1.0","source":{"id":"2311.13277","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.13277","created_at":"2026-07-05T07:53:32Z"},{"alias_kind":"arxiv_version","alias_value":"2311.13277v2","created_at":"2026-07-05T07:53:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.13277","created_at":"2026-07-05T07:53:32Z"},{"alias_kind":"pith_short_12","alias_value":"76CBTVULSR5D","created_at":"2026-07-05T07:53:32Z"},{"alias_kind":"pith_short_16","alias_value":"76CBTVULSR5DC2SC","created_at":"2026-07-05T07:53:32Z"},{"alias_kind":"pith_short_8","alias_value":"76CBTVUL","created_at":"2026-07-05T07:53:32Z"}],"graph_snapshots":[{"event_id":"sha256:0e2f6531df82bfcdf9d6f3bf221a9bfd91e7d6f34264a144171b3894c386feb2","target":"graph","created_at":"2026-07-05T07:53:32Z","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/2311.13277/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Matrix factorization (MF) is a simple collaborative filtering technique that achieves superior recommendation accuracy by decomposing the user-item interaction matrix into user and item latent matrices. Because the model typically learns each interaction independently, it may overlook the underlying shared dependencies between users and items, resulting in less stable and interpretable recommendations. Based on these insights, we propose \"Hierarchical Matrix Factorization\" (HMF), which incorporates clustering concepts to capture the hierarchy, where leaf nodes and other nodes correspond to use","authors_text":"Kai Sugahara, Kazushi Okamoto","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2023-11-22T09:53:57Z","title":"Hierarchical Matrix Factorization for Interpretable Collaborative Filtering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.13277","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:f39fcc5be5efa72c4210f6e74517406e4c1315e287a6274659c2edefa7cb8290","target":"record","created_at":"2026-07-05T07:53:32Z","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":"e11b8998bcb2dca7b213e04b8b44e0dc94707658dbb8600c74c94fbe51b23052","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2023-11-22T09:53:57Z","title_canon_sha256":"badb18f2a6a09dcf41a3ade6edee2f1f0c9d5c693d37a5d5c6cf0658ed3d4807"},"schema_version":"1.0","source":{"id":"2311.13277","kind":"arxiv","version":2}},"canonical_sha256":"ff8419d68b947a316a42f663492791762fe2859ada3aa96802fc786702d3653f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ff8419d68b947a316a42f663492791762fe2859ada3aa96802fc786702d3653f","first_computed_at":"2026-07-05T07:53:32.097340Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:53:32.097340Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"t9IkuiGD9Fh1CIL4ddhklGsxfJQzU3ACe1Mq+bGTdQodAcHurEJde2nlf5iD5AOuODz/WQwc8iTXxd27KrV3BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:53:32.097770Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.13277","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f39fcc5be5efa72c4210f6e74517406e4c1315e287a6274659c2edefa7cb8290","sha256:0e2f6531df82bfcdf9d6f3bf221a9bfd91e7d6f34264a144171b3894c386feb2"],"state_sha256":"a85105a9da8f99b4ab283e92de039cc7d35f7743d8cfaf579082357441bec52e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q97QLuni1fQpKz81HoYldEVH7ZD8usF2s/F3damx10HTgRLjrHYlNX4CRXwT4JXGS2mwsBIe8JVjHe5/uCmYBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T17:29:07.427083Z","bundle_sha256":"aea431fc6e4a9ccb75532059c8a6301d33adcd5418136d3808ebaaa5d3f16c92"}}