{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:I3CIZPJWGKKPRJW3KKZGM5IVF3","short_pith_number":"pith:I3CIZPJW","canonical_record":{"source":{"id":"1810.10175","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-10-24T03:56:07Z","cross_cats_sorted":[],"title_canon_sha256":"ba3f1446ac37446600dd7afc555560306c4d4ed617f692b45523271ef7a3efb0","abstract_canon_sha256":"743a76e4fb4e5176101095469ff26232027dc1c7f128c99279d781c886fb2fe9"},"schema_version":"1.0"},"canonical_sha256":"46c48cbd363294f8a6db52b26675152ed6c710cdefc815356872ab54050f2b9f","source":{"kind":"arxiv","id":"1810.10175","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.10175","created_at":"2026-05-18T00:02:24Z"},{"alias_kind":"arxiv_version","alias_value":"1810.10175v1","created_at":"2026-05-18T00:02:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.10175","created_at":"2026-05-18T00:02:24Z"},{"alias_kind":"pith_short_12","alias_value":"I3CIZPJWGKKP","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"I3CIZPJWGKKPRJW3","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"I3CIZPJW","created_at":"2026-05-18T12:32:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:I3CIZPJWGKKPRJW3KKZGM5IVF3","target":"record","payload":{"canonical_record":{"source":{"id":"1810.10175","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-10-24T03:56:07Z","cross_cats_sorted":[],"title_canon_sha256":"ba3f1446ac37446600dd7afc555560306c4d4ed617f692b45523271ef7a3efb0","abstract_canon_sha256":"743a76e4fb4e5176101095469ff26232027dc1c7f128c99279d781c886fb2fe9"},"schema_version":"1.0"},"canonical_sha256":"46c48cbd363294f8a6db52b26675152ed6c710cdefc815356872ab54050f2b9f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:02:24.009719Z","signature_b64":"tC2DZ6ZCGh5JMCqBfpUKiYowzmbT2W8vNsFkINefKCWl/4Yir1988/9A6+NQOuJvW+MiyYUBOgi2hjfHuAGgCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"46c48cbd363294f8a6db52b26675152ed6c710cdefc815356872ab54050f2b9f","last_reissued_at":"2026-05-18T00:02:24.009193Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:02:24.009193Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.10175","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":"2026-05-18T00:02:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eeNT0R5to1Mhm3n0K0Sy1PUF2KrnbpIygkvY4BwoIbKhuZmp/lFLzX4CBk9YDbJemlezOTJ3MC0Ojo1GYcLlBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T23:12:44.062434Z"},"content_sha256":"80809d46852de17b7b512618f34ef8935f76f68d1e85e812c0090f510b38275d","schema_version":"1.0","event_id":"sha256:80809d46852de17b7b512618f34ef8935f76f68d1e85e812c0090f510b38275d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:I3CIZPJWGKKPRJW3KKZGM5IVF3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Data-driven Blockbuster Planning on Online Movie Knowledge Library","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Chenwei Zhang, Jiawei Zhang, Philip S. Yu, Ye Liu","submitted_at":"2018-10-24T03:56:07Z","abstract_excerpt":"In the era of big data, logistic planning can be made data-driven to take advantage of accumulated knowledge in the past. While in the movie industry, movie planning can also exploit the existing online movie knowledge library to achieve better results. However, it is ineffective to solely rely on conventional heuristics for movie planning, due to a large number of existing movies and various real-world factors that contribute to the success of each movie, such as the movie genre, available budget, production team (involving actor, actress, director, and writer), etc. In this paper, we study a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.10175","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":"2026-05-18T00:02:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tL+ROtMok1dGJsHqZu/BsWkin52O2coUprJ7OW1p7+UcM11/+pZ/biNIZVHyo0a5tH/dwG9Fl7pGurM39e3bBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T23:12:44.063367Z"},"content_sha256":"46eb82533573b1583223ed56354f72ce3ad9555a475d94b733eff2213c520c77","schema_version":"1.0","event_id":"sha256:46eb82533573b1583223ed56354f72ce3ad9555a475d94b733eff2213c520c77"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/I3CIZPJWGKKPRJW3KKZGM5IVF3/bundle.json","state_url":"https://pith.science/pith/I3CIZPJWGKKPRJW3KKZGM5IVF3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/I3CIZPJWGKKPRJW3KKZGM5IVF3/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":"2026-05-30T23:12:44Z","links":{"resolver":"https://pith.science/pith/I3CIZPJWGKKPRJW3KKZGM5IVF3","bundle":"https://pith.science/pith/I3CIZPJWGKKPRJW3KKZGM5IVF3/bundle.json","state":"https://pith.science/pith/I3CIZPJWGKKPRJW3KKZGM5IVF3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/I3CIZPJWGKKPRJW3KKZGM5IVF3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:I3CIZPJWGKKPRJW3KKZGM5IVF3","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":"743a76e4fb4e5176101095469ff26232027dc1c7f128c99279d781c886fb2fe9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-10-24T03:56:07Z","title_canon_sha256":"ba3f1446ac37446600dd7afc555560306c4d4ed617f692b45523271ef7a3efb0"},"schema_version":"1.0","source":{"id":"1810.10175","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.10175","created_at":"2026-05-18T00:02:24Z"},{"alias_kind":"arxiv_version","alias_value":"1810.10175v1","created_at":"2026-05-18T00:02:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.10175","created_at":"2026-05-18T00:02:24Z"},{"alias_kind":"pith_short_12","alias_value":"I3CIZPJWGKKP","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"I3CIZPJWGKKPRJW3","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"I3CIZPJW","created_at":"2026-05-18T12:32:28Z"}],"graph_snapshots":[{"event_id":"sha256:46eb82533573b1583223ed56354f72ce3ad9555a475d94b733eff2213c520c77","target":"graph","created_at":"2026-05-18T00:02:24Z","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 the era of big data, logistic planning can be made data-driven to take advantage of accumulated knowledge in the past. While in the movie industry, movie planning can also exploit the existing online movie knowledge library to achieve better results. However, it is ineffective to solely rely on conventional heuristics for movie planning, due to a large number of existing movies and various real-world factors that contribute to the success of each movie, such as the movie genre, available budget, production team (involving actor, actress, director, and writer), etc. In this paper, we study a","authors_text":"Chenwei Zhang, Jiawei Zhang, Philip S. Yu, Ye Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-10-24T03:56:07Z","title":"Data-driven Blockbuster Planning on Online Movie Knowledge Library"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.10175","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":"sha256:80809d46852de17b7b512618f34ef8935f76f68d1e85e812c0090f510b38275d","target":"record","created_at":"2026-05-18T00:02:24Z","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":"743a76e4fb4e5176101095469ff26232027dc1c7f128c99279d781c886fb2fe9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-10-24T03:56:07Z","title_canon_sha256":"ba3f1446ac37446600dd7afc555560306c4d4ed617f692b45523271ef7a3efb0"},"schema_version":"1.0","source":{"id":"1810.10175","kind":"arxiv","version":1}},"canonical_sha256":"46c48cbd363294f8a6db52b26675152ed6c710cdefc815356872ab54050f2b9f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"46c48cbd363294f8a6db52b26675152ed6c710cdefc815356872ab54050f2b9f","first_computed_at":"2026-05-18T00:02:24.009193Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:02:24.009193Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tC2DZ6ZCGh5JMCqBfpUKiYowzmbT2W8vNsFkINefKCWl/4Yir1988/9A6+NQOuJvW+MiyYUBOgi2hjfHuAGgCw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:02:24.009719Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.10175","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:80809d46852de17b7b512618f34ef8935f76f68d1e85e812c0090f510b38275d","sha256:46eb82533573b1583223ed56354f72ce3ad9555a475d94b733eff2213c520c77"],"state_sha256":"9927decf266dc91bcc0db92b81da2f63b2d41abe603cfca20e2ea0e53e50386a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uubFk0oPPXV3Vsg75hVOjVkhW6XYRNDn+KffgSbUAd3b5dKpDlI59bCnyLMQic+Yt3t+jmZJNv1fnDdsv8v+Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T23:12:44.067669Z","bundle_sha256":"20c83488c16c881b5de69e9f70fe9f14faa2b4a466704d1b33f0d82b82b65a27"}}