{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:UJEPQUOJXR2JEA42DBPWFLM3L7","short_pith_number":"pith:UJEPQUOJ","canonical_record":{"source":{"id":"1709.06810","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2017-09-20T10:55:22Z","cross_cats_sorted":["cs.DS"],"title_canon_sha256":"82c146d29d323fefdbe28228ad86ea02b4c37a53b9592805378f7707063f1dac","abstract_canon_sha256":"2db1dec88235d8ae79faf146c2b418b119fcde68da2dcd93e0e240eeec1eade2"},"schema_version":"1.0"},"canonical_sha256":"a248f851c9bc7492039a185f62ad9b5fd3cb66a3448d503649fcb870810c8574","source":{"kind":"arxiv","id":"1709.06810","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.06810","created_at":"2026-05-18T00:33:58Z"},{"alias_kind":"arxiv_version","alias_value":"1709.06810v2","created_at":"2026-05-18T00:33:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.06810","created_at":"2026-05-18T00:33:58Z"},{"alias_kind":"pith_short_12","alias_value":"UJEPQUOJXR2J","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"UJEPQUOJXR2JEA42","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"UJEPQUOJ","created_at":"2026-05-18T12:31:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:UJEPQUOJXR2JEA42DBPWFLM3L7","target":"record","payload":{"canonical_record":{"source":{"id":"1709.06810","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2017-09-20T10:55:22Z","cross_cats_sorted":["cs.DS"],"title_canon_sha256":"82c146d29d323fefdbe28228ad86ea02b4c37a53b9592805378f7707063f1dac","abstract_canon_sha256":"2db1dec88235d8ae79faf146c2b418b119fcde68da2dcd93e0e240eeec1eade2"},"schema_version":"1.0"},"canonical_sha256":"a248f851c9bc7492039a185f62ad9b5fd3cb66a3448d503649fcb870810c8574","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:33:58.364141Z","signature_b64":"VaOc9yuYA4ZXuS7cVEigWEhUs38zqkrVs0TZ7Yb9y7aEHytCQBK9aRRduIUyg+XGWz1YJJX8SVISd9b49/mnDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a248f851c9bc7492039a185f62ad9b5fd3cb66a3448d503649fcb870810c8574","last_reissued_at":"2026-05-18T00:33:58.363513Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:33:58.363513Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1709.06810","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":"2026-05-18T00:33:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zY+Ray9o3DtAxviFThQlegriVnriTM7lgCLL1Jd+d4tAwqXzQm6NdEmQgEYVSgj9zswVTc8qnNkVzgTI0bpSDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T09:09:03.792500Z"},"content_sha256":"5dc700ae850f0b1f2436da65aff62a0139894a49fe566c4787aa4528b19bdd79","schema_version":"1.0","event_id":"sha256:5dc700ae850f0b1f2436da65aff62a0139894a49fe566c4787aa4528b19bdd79"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:UJEPQUOJXR2JEA42DBPWFLM3L7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient Graph Edit Distance Computation and Verification via Anchor-aware Lower Bound Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DS"],"primary_cat":"cs.DB","authors_text":"Lijun Chang, Lu Qin, Wenjie Zhang, Xing Feng, Xuemin Lin","submitted_at":"2017-09-20T10:55:22Z","abstract_excerpt":"Graph edit distance (GED) is an important similarity measure adopted in a similarity-based analysis between two graphs, and computing GED is a primitive operator in graph database analysis. Partially due to the NP-hardness, the existing techniques for computing GED are only able to process very small graphs with less than 30 vertices. Motivated by this, in this paper we systematically study the problems of both GED computation, and GED verification (i.e., verify whether the GED between two graphs is no larger than a user-given threshold). Firstly, we develop a unified framework that can be ins"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.06810","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":""},"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":"2026-05-18T00:33:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u2nYnhHmCo1dVo2t6jNRV3FWUMpIMTDM7d446plKCWzzooo/qDjsnDDIyolr7ifvXN63KvBIyNxJNKpeT6GSCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T09:09:03.793408Z"},"content_sha256":"9ccecb488f54c5da9da496b5576d02b4ff971bae55a3dec556c680a42412c142","schema_version":"1.0","event_id":"sha256:9ccecb488f54c5da9da496b5576d02b4ff971bae55a3dec556c680a42412c142"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UJEPQUOJXR2JEA42DBPWFLM3L7/bundle.json","state_url":"https://pith.science/pith/UJEPQUOJXR2JEA42DBPWFLM3L7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UJEPQUOJXR2JEA42DBPWFLM3L7/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":"2026-05-31T09:09:03Z","links":{"resolver":"https://pith.science/pith/UJEPQUOJXR2JEA42DBPWFLM3L7","bundle":"https://pith.science/pith/UJEPQUOJXR2JEA42DBPWFLM3L7/bundle.json","state":"https://pith.science/pith/UJEPQUOJXR2JEA42DBPWFLM3L7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UJEPQUOJXR2JEA42DBPWFLM3L7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:UJEPQUOJXR2JEA42DBPWFLM3L7","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":"2db1dec88235d8ae79faf146c2b418b119fcde68da2dcd93e0e240eeec1eade2","cross_cats_sorted":["cs.DS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2017-09-20T10:55:22Z","title_canon_sha256":"82c146d29d323fefdbe28228ad86ea02b4c37a53b9592805378f7707063f1dac"},"schema_version":"1.0","source":{"id":"1709.06810","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.06810","created_at":"2026-05-18T00:33:58Z"},{"alias_kind":"arxiv_version","alias_value":"1709.06810v2","created_at":"2026-05-18T00:33:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.06810","created_at":"2026-05-18T00:33:58Z"},{"alias_kind":"pith_short_12","alias_value":"UJEPQUOJXR2J","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"UJEPQUOJXR2JEA42","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"UJEPQUOJ","created_at":"2026-05-18T12:31:46Z"}],"graph_snapshots":[{"event_id":"sha256:9ccecb488f54c5da9da496b5576d02b4ff971bae55a3dec556c680a42412c142","target":"graph","created_at":"2026-05-18T00:33:58Z","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":"Graph edit distance (GED) is an important similarity measure adopted in a similarity-based analysis between two graphs, and computing GED is a primitive operator in graph database analysis. Partially due to the NP-hardness, the existing techniques for computing GED are only able to process very small graphs with less than 30 vertices. Motivated by this, in this paper we systematically study the problems of both GED computation, and GED verification (i.e., verify whether the GED between two graphs is no larger than a user-given threshold). Firstly, we develop a unified framework that can be ins","authors_text":"Lijun Chang, Lu Qin, Wenjie Zhang, Xing Feng, Xuemin Lin","cross_cats":["cs.DS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2017-09-20T10:55:22Z","title":"Efficient Graph Edit Distance Computation and Verification via Anchor-aware Lower Bound Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.06810","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":"sha256:5dc700ae850f0b1f2436da65aff62a0139894a49fe566c4787aa4528b19bdd79","target":"record","created_at":"2026-05-18T00:33:58Z","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":"2db1dec88235d8ae79faf146c2b418b119fcde68da2dcd93e0e240eeec1eade2","cross_cats_sorted":["cs.DS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2017-09-20T10:55:22Z","title_canon_sha256":"82c146d29d323fefdbe28228ad86ea02b4c37a53b9592805378f7707063f1dac"},"schema_version":"1.0","source":{"id":"1709.06810","kind":"arxiv","version":2}},"canonical_sha256":"a248f851c9bc7492039a185f62ad9b5fd3cb66a3448d503649fcb870810c8574","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a248f851c9bc7492039a185f62ad9b5fd3cb66a3448d503649fcb870810c8574","first_computed_at":"2026-05-18T00:33:58.363513Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:33:58.363513Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VaOc9yuYA4ZXuS7cVEigWEhUs38zqkrVs0TZ7Yb9y7aEHytCQBK9aRRduIUyg+XGWz1YJJX8SVISd9b49/mnDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:33:58.364141Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.06810","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5dc700ae850f0b1f2436da65aff62a0139894a49fe566c4787aa4528b19bdd79","sha256:9ccecb488f54c5da9da496b5576d02b4ff971bae55a3dec556c680a42412c142"],"state_sha256":"1ee232487f39ca93c5baa5f226e054a54ea755e49017ad97f482e04a0636a5ae"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h0bg3CaZjON47wV33WNXbD24DvwiZ5LeZT5ZCWvGuX0FWWQDYk9CShOon0mZUPET/enAMCAf71bgROtapsJFDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T09:09:03.799410Z","bundle_sha256":"cd09d19baad6139fd780fa4e9ff3b913f0361bb2b4c6fa54dcbce11ba6e52d8f"}}