{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:2CIKD2K4TQSI72NBPE7UAM7N3A","short_pith_number":"pith:2CIKD2K4","canonical_record":{"source":{"id":"2309.16102","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-09-28T01:57:40Z","cross_cats_sorted":["cs.DB"],"title_canon_sha256":"ed892cb41124e4186b1ba6acc22a62063a06e2125baf857ce2fe08bf692e7ebc","abstract_canon_sha256":"42d7fac4330f012685586de92b36084774689a9df7c2c19950916d079f544268"},"schema_version":"1.0"},"canonical_sha256":"d090a1e95c9c248fe9a1793f4033edd819c9519f6712e31784fe8c5e71c2a8b2","source":{"kind":"arxiv","id":"2309.16102","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.16102","created_at":"2026-07-05T06:55:11Z"},{"alias_kind":"arxiv_version","alias_value":"2309.16102v1","created_at":"2026-07-05T06:55:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.16102","created_at":"2026-07-05T06:55:11Z"},{"alias_kind":"pith_short_12","alias_value":"2CIKD2K4TQSI","created_at":"2026-07-05T06:55:11Z"},{"alias_kind":"pith_short_16","alias_value":"2CIKD2K4TQSI72NB","created_at":"2026-07-05T06:55:11Z"},{"alias_kind":"pith_short_8","alias_value":"2CIKD2K4","created_at":"2026-07-05T06:55:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:2CIKD2K4TQSI72NBPE7UAM7N3A","target":"record","payload":{"canonical_record":{"source":{"id":"2309.16102","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-09-28T01:57:40Z","cross_cats_sorted":["cs.DB"],"title_canon_sha256":"ed892cb41124e4186b1ba6acc22a62063a06e2125baf857ce2fe08bf692e7ebc","abstract_canon_sha256":"42d7fac4330f012685586de92b36084774689a9df7c2c19950916d079f544268"},"schema_version":"1.0"},"canonical_sha256":"d090a1e95c9c248fe9a1793f4033edd819c9519f6712e31784fe8c5e71c2a8b2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:55:11.548000Z","signature_b64":"LLajOH0lgHKaTttz+ui/xhklG2FqbCZKqyIvFxuOnGk+yw6TNsG5fx8w1Nv8L7fltKR8YKZTPrWaMxtTU7VMAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d090a1e95c9c248fe9a1793f4033edd819c9519f6712e31784fe8c5e71c2a8b2","last_reissued_at":"2026-07-05T06:55:11.547594Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:55:11.547594Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2309.16102","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":"2026-07-05T06:55:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JvTaApKFrFWtUoyz+9CqOc0dP9N+q/g9PYVX1RfzrJHnDGDXNo2ov8fMqYCkdJ2mASIG6ZX2vs44u35CbUAHDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T08:36:38.413435Z"},"content_sha256":"9cb4aabec77112fb88d05ebd146bef5ca807d183026c4fac0a1bbd2b4d8ac8a6","schema_version":"1.0","event_id":"sha256:9cb4aabec77112fb88d05ebd146bef5ca807d183026c4fac0a1bbd2b4d8ac8a6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:2CIKD2K4TQSI72NBPE7UAM7N3A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Discovering Utility-driven Interval Rules","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DB"],"primary_cat":"cs.AI","authors_text":"Chunkai Zhang, Huaijin Hao, Maohua Lyu, Philip S. Yu, Wensheng Gan","submitted_at":"2023-09-28T01:57:40Z","abstract_excerpt":"For artificial intelligence, high-utility sequential rule mining (HUSRM) is a knowledge discovery method that can reveal the associations between events in the sequences. Recently, abundant methods have been proposed to discover high-utility sequence rules. However, the existing methods are all related to point-based sequences. Interval events that persist for some time are common. Traditional interval-event sequence knowledge discovery tasks mainly focus on pattern discovery, but patterns cannot reveal the correlation between interval events well. Moreover, the existing HUSRM algorithms canno"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.16102","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/2309.16102/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":"2026-07-05T06:55:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PLQyXJFv81tJiA4+LfCQGVgCa+dL0YdjYm+rFArcI8FHrFJmQKa2gJne6aDN9190Lpe7tLYSnLKbew/xTu5dCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T08:36:38.413991Z"},"content_sha256":"8481449d4393565c02d11b74c7aaa68d73fd4a5b4838e0ec55d9f29e88743aac","schema_version":"1.0","event_id":"sha256:8481449d4393565c02d11b74c7aaa68d73fd4a5b4838e0ec55d9f29e88743aac"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2CIKD2K4TQSI72NBPE7UAM7N3A/bundle.json","state_url":"https://pith.science/pith/2CIKD2K4TQSI72NBPE7UAM7N3A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2CIKD2K4TQSI72NBPE7UAM7N3A/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":"2026-08-04T08:36:38Z","links":{"resolver":"https://pith.science/pith/2CIKD2K4TQSI72NBPE7UAM7N3A","bundle":"https://pith.science/pith/2CIKD2K4TQSI72NBPE7UAM7N3A/bundle.json","state":"https://pith.science/pith/2CIKD2K4TQSI72NBPE7UAM7N3A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2CIKD2K4TQSI72NBPE7UAM7N3A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:2CIKD2K4TQSI72NBPE7UAM7N3A","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":"42d7fac4330f012685586de92b36084774689a9df7c2c19950916d079f544268","cross_cats_sorted":["cs.DB"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-09-28T01:57:40Z","title_canon_sha256":"ed892cb41124e4186b1ba6acc22a62063a06e2125baf857ce2fe08bf692e7ebc"},"schema_version":"1.0","source":{"id":"2309.16102","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.16102","created_at":"2026-07-05T06:55:11Z"},{"alias_kind":"arxiv_version","alias_value":"2309.16102v1","created_at":"2026-07-05T06:55:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.16102","created_at":"2026-07-05T06:55:11Z"},{"alias_kind":"pith_short_12","alias_value":"2CIKD2K4TQSI","created_at":"2026-07-05T06:55:11Z"},{"alias_kind":"pith_short_16","alias_value":"2CIKD2K4TQSI72NB","created_at":"2026-07-05T06:55:11Z"},{"alias_kind":"pith_short_8","alias_value":"2CIKD2K4","created_at":"2026-07-05T06:55:11Z"}],"graph_snapshots":[{"event_id":"sha256:8481449d4393565c02d11b74c7aaa68d73fd4a5b4838e0ec55d9f29e88743aac","target":"graph","created_at":"2026-07-05T06:55:11Z","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/2309.16102/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"For artificial intelligence, high-utility sequential rule mining (HUSRM) is a knowledge discovery method that can reveal the associations between events in the sequences. Recently, abundant methods have been proposed to discover high-utility sequence rules. However, the existing methods are all related to point-based sequences. Interval events that persist for some time are common. Traditional interval-event sequence knowledge discovery tasks mainly focus on pattern discovery, but patterns cannot reveal the correlation between interval events well. Moreover, the existing HUSRM algorithms canno","authors_text":"Chunkai Zhang, Huaijin Hao, Maohua Lyu, Philip S. Yu, Wensheng Gan","cross_cats":["cs.DB"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-09-28T01:57:40Z","title":"Discovering Utility-driven Interval Rules"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.16102","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":"sha256:9cb4aabec77112fb88d05ebd146bef5ca807d183026c4fac0a1bbd2b4d8ac8a6","target":"record","created_at":"2026-07-05T06:55:11Z","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":"42d7fac4330f012685586de92b36084774689a9df7c2c19950916d079f544268","cross_cats_sorted":["cs.DB"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-09-28T01:57:40Z","title_canon_sha256":"ed892cb41124e4186b1ba6acc22a62063a06e2125baf857ce2fe08bf692e7ebc"},"schema_version":"1.0","source":{"id":"2309.16102","kind":"arxiv","version":1}},"canonical_sha256":"d090a1e95c9c248fe9a1793f4033edd819c9519f6712e31784fe8c5e71c2a8b2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d090a1e95c9c248fe9a1793f4033edd819c9519f6712e31784fe8c5e71c2a8b2","first_computed_at":"2026-07-05T06:55:11.547594Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:55:11.547594Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LLajOH0lgHKaTttz+ui/xhklG2FqbCZKqyIvFxuOnGk+yw6TNsG5fx8w1Nv8L7fltKR8YKZTPrWaMxtTU7VMAA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:55:11.548000Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.16102","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9cb4aabec77112fb88d05ebd146bef5ca807d183026c4fac0a1bbd2b4d8ac8a6","sha256:8481449d4393565c02d11b74c7aaa68d73fd4a5b4838e0ec55d9f29e88743aac"],"state_sha256":"7bfca5964f4bee7630bf92fa5ee4a80e97614df7659f8698c636e61a70925ce9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C2MqVIcX/kyzhbj2pKs3XyH24XHO6bH1smn+iHAld6L4hC8yj1xdw18ly8A8u+uIBzTeP/+l/ztUFI37zatBAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T08:36:38.417961Z","bundle_sha256":"b9d18410b2e906b46f8e2b6e2ed26b3823e35251cf3aa499a5e70955acc3ebf0"}}