{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2011:SM4DPA36EDI6SGHEBKG3EREJ5C","short_pith_number":"pith:SM4DPA36","canonical_record":{"source":{"id":"1109.4684","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2011-09-22T00:56:22Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"dac0a71ea93392c88336bf4d189892a459bdcf16879debfe9b8509bf6eb91a02","abstract_canon_sha256":"c1b466f2904468cdceb92aa1b64437629ce44ea7b2e3614c4cb07f7520a6b336"},"schema_version":"1.0"},"canonical_sha256":"933837837e20d1e918e40a8db24489e88bdc0b10c7bf6d6ca5498b358a67b004","source":{"kind":"arxiv","id":"1109.4684","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1109.4684","created_at":"2026-05-18T02:21:36Z"},{"alias_kind":"arxiv_version","alias_value":"1109.4684v1","created_at":"2026-05-18T02:21:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1109.4684","created_at":"2026-05-18T02:21:36Z"},{"alias_kind":"pith_short_12","alias_value":"SM4DPA36EDI6","created_at":"2026-05-18T12:26:41Z"},{"alias_kind":"pith_short_16","alias_value":"SM4DPA36EDI6SGHE","created_at":"2026-05-18T12:26:41Z"},{"alias_kind":"pith_short_8","alias_value":"SM4DPA36","created_at":"2026-05-18T12:26:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2011:SM4DPA36EDI6SGHEBKG3EREJ5C","target":"record","payload":{"canonical_record":{"source":{"id":"1109.4684","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2011-09-22T00:56:22Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"dac0a71ea93392c88336bf4d189892a459bdcf16879debfe9b8509bf6eb91a02","abstract_canon_sha256":"c1b466f2904468cdceb92aa1b64437629ce44ea7b2e3614c4cb07f7520a6b336"},"schema_version":"1.0"},"canonical_sha256":"933837837e20d1e918e40a8db24489e88bdc0b10c7bf6d6ca5498b358a67b004","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:21:36.376100Z","signature_b64":"ipxpb4yDLe/5WUUlQKvCoql+N/AzzUmGrgSHQarRphXH1a2Oz0kUnH5pWsb7PU+LjtYh92++zKI1xc5icndBAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"933837837e20d1e918e40a8db24489e88bdc0b10c7bf6d6ca5498b358a67b004","last_reissued_at":"2026-05-18T02:21:36.375654Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:21:36.375654Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1109.4684","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":"2026-05-18T02:21:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"m6CnmVTGfS89GitIfoZ1wMTzctJ55ZTUkH58f4s5wCxxU+k2unA8gWpJZPqu2Y7kW/4tZEXgP130Y/wk1xcQCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T20:22:34.108913Z"},"content_sha256":"1240f93395460abcdae4a28a4c6e55dab92a4081642ca6614c9a2308d5e30183","schema_version":"1.0","event_id":"sha256:1240f93395460abcdae4a28a4c6e55dab92a4081642ca6614c9a2308d5e30183"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2011:SM4DPA36EDI6SGHEBKG3EREJ5C","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Exhaustive and Efficient Constraint Propagation: A Semi-Supervised Learning Perspective and Its Applications","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.AI","authors_text":"Horace H.S. Ip, Yuxin Peng, Zhiwu Lu","submitted_at":"2011-09-22T00:56:22Z","abstract_excerpt":"This paper presents a novel pairwise constraint propagation approach by decomposing the challenging constraint propagation problem into a set of independent semi-supervised learning subproblems which can be solved in quadratic time using label propagation based on k-nearest neighbor graphs. Considering that this time cost is proportional to the number of all possible pairwise constraints, our approach actually provides an efficient solution for exhaustively propagating pairwise constraints throughout the entire dataset. The resulting exhaustive set of propagated pairwise constraints are furthe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1109.4684","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":"2026-05-18T02:21:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pAQN9Jz/p4QeEqxxow3vyfy3Ba6dtjrJ9OisbnJG9flScft9V+9teN7TX3mBMt/5/gX5gT3j/IwNiY6yNgExDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T20:22:34.109455Z"},"content_sha256":"9a9a902c5a42258f85f9f39cb4c6cee71016aa0313d9672fde3fa4c24114602b","schema_version":"1.0","event_id":"sha256:9a9a902c5a42258f85f9f39cb4c6cee71016aa0313d9672fde3fa4c24114602b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SM4DPA36EDI6SGHEBKG3EREJ5C/bundle.json","state_url":"https://pith.science/pith/SM4DPA36EDI6SGHEBKG3EREJ5C/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SM4DPA36EDI6SGHEBKG3EREJ5C/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":"2026-05-27T20:22:34Z","links":{"resolver":"https://pith.science/pith/SM4DPA36EDI6SGHEBKG3EREJ5C","bundle":"https://pith.science/pith/SM4DPA36EDI6SGHEBKG3EREJ5C/bundle.json","state":"https://pith.science/pith/SM4DPA36EDI6SGHEBKG3EREJ5C/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SM4DPA36EDI6SGHEBKG3EREJ5C/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2011:SM4DPA36EDI6SGHEBKG3EREJ5C","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":"c1b466f2904468cdceb92aa1b64437629ce44ea7b2e3614c4cb07f7520a6b336","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2011-09-22T00:56:22Z","title_canon_sha256":"dac0a71ea93392c88336bf4d189892a459bdcf16879debfe9b8509bf6eb91a02"},"schema_version":"1.0","source":{"id":"1109.4684","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1109.4684","created_at":"2026-05-18T02:21:36Z"},{"alias_kind":"arxiv_version","alias_value":"1109.4684v1","created_at":"2026-05-18T02:21:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1109.4684","created_at":"2026-05-18T02:21:36Z"},{"alias_kind":"pith_short_12","alias_value":"SM4DPA36EDI6","created_at":"2026-05-18T12:26:41Z"},{"alias_kind":"pith_short_16","alias_value":"SM4DPA36EDI6SGHE","created_at":"2026-05-18T12:26:41Z"},{"alias_kind":"pith_short_8","alias_value":"SM4DPA36","created_at":"2026-05-18T12:26:41Z"}],"graph_snapshots":[{"event_id":"sha256:9a9a902c5a42258f85f9f39cb4c6cee71016aa0313d9672fde3fa4c24114602b","target":"graph","created_at":"2026-05-18T02:21:36Z","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":"This paper presents a novel pairwise constraint propagation approach by decomposing the challenging constraint propagation problem into a set of independent semi-supervised learning subproblems which can be solved in quadratic time using label propagation based on k-nearest neighbor graphs. Considering that this time cost is proportional to the number of all possible pairwise constraints, our approach actually provides an efficient solution for exhaustively propagating pairwise constraints throughout the entire dataset. The resulting exhaustive set of propagated pairwise constraints are furthe","authors_text":"Horace H.S. Ip, Yuxin Peng, Zhiwu Lu","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2011-09-22T00:56:22Z","title":"Exhaustive and Efficient Constraint Propagation: A Semi-Supervised Learning Perspective and Its Applications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1109.4684","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":"sha256:1240f93395460abcdae4a28a4c6e55dab92a4081642ca6614c9a2308d5e30183","target":"record","created_at":"2026-05-18T02:21:36Z","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":"c1b466f2904468cdceb92aa1b64437629ce44ea7b2e3614c4cb07f7520a6b336","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2011-09-22T00:56:22Z","title_canon_sha256":"dac0a71ea93392c88336bf4d189892a459bdcf16879debfe9b8509bf6eb91a02"},"schema_version":"1.0","source":{"id":"1109.4684","kind":"arxiv","version":1}},"canonical_sha256":"933837837e20d1e918e40a8db24489e88bdc0b10c7bf6d6ca5498b358a67b004","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"933837837e20d1e918e40a8db24489e88bdc0b10c7bf6d6ca5498b358a67b004","first_computed_at":"2026-05-18T02:21:36.375654Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:21:36.375654Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ipxpb4yDLe/5WUUlQKvCoql+N/AzzUmGrgSHQarRphXH1a2Oz0kUnH5pWsb7PU+LjtYh92++zKI1xc5icndBAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T02:21:36.376100Z","signed_message":"canonical_sha256_bytes"},"source_id":"1109.4684","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1240f93395460abcdae4a28a4c6e55dab92a4081642ca6614c9a2308d5e30183","sha256:9a9a902c5a42258f85f9f39cb4c6cee71016aa0313d9672fde3fa4c24114602b"],"state_sha256":"c5f728278243f5ff8b03997ce8d1db62ecc2c4364a04246ada6b4aa11d53706e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BQVm59hxRKnozoxyRSReuAEmWdDJ7kQZh1h/ffRN2NRoXeAVtniz9TFCqokt+O0BuzoAGZI8N5TTkh8JDk8HDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T20:22:34.113104Z","bundle_sha256":"51a6e7663e5da401393481ce409cd3ec74d8e58d0a3d1ce9a336767cec18d80a"}}