{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:DC55LTB633DQLGY4EYE3WVLMF7","short_pith_number":"pith:DC55LTB6","schema_version":"1.0","canonical_sha256":"18bbd5cc3edec7059b1c2609bb556c2fc48680961e967371764d637eef823f46","source":{"kind":"arxiv","id":"1304.1424","version":2},"attestation_state":"computed","paper":{"title":"Improved approximation for 3-dimensional matching via bounded pathwidth local search","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Marek Cygan","submitted_at":"2013-04-04T16:34:44Z","abstract_excerpt":"One of the most natural optimization problems is the k-Set Packing problem, where given a family of sets of size at most k one should select a maximum size subfamily of pairwise disjoint sets. A special case of 3-Set Packing is the well known 3-Dimensional Matching problem. Both problems belong to the Karp`s list of 21 NP-complete problems. The best known polynomial time approximation ratio for k-Set Packing is (k + eps)/2 and goes back to the work of Hurkens and Schrijver [SIDMA`89], which gives (1.5 + eps)-approximation for 3-Dimensional Matching. Those results are obtained by a simple local"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1304.1424","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2013-04-04T16:34:44Z","cross_cats_sorted":[],"title_canon_sha256":"ca5c6f315cbc8a63b73ecd1dd0764fb3268255ca9e55f4dbb6a6945f993e4d49","abstract_canon_sha256":"8f1b434cc01372c13fc423609af0b66a53fbbb5c2773e0d707597e0ee69d426b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:15:34.230423Z","signature_b64":"Xxu5lotdq56OOSlRI602BnGbk+7scd/w0gwV0OBjA947zH6Fgw/zFCra3wrG4ySq3Mr7I8/8VKTKIKHZuHHYBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"18bbd5cc3edec7059b1c2609bb556c2fc48680961e967371764d637eef823f46","last_reissued_at":"2026-05-18T03:15:34.229863Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:15:34.229863Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Improved approximation for 3-dimensional matching via bounded pathwidth local search","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Marek Cygan","submitted_at":"2013-04-04T16:34:44Z","abstract_excerpt":"One of the most natural optimization problems is the k-Set Packing problem, where given a family of sets of size at most k one should select a maximum size subfamily of pairwise disjoint sets. A special case of 3-Set Packing is the well known 3-Dimensional Matching problem. Both problems belong to the Karp`s list of 21 NP-complete problems. The best known polynomial time approximation ratio for k-Set Packing is (k + eps)/2 and goes back to the work of Hurkens and Schrijver [SIDMA`89], which gives (1.5 + eps)-approximation for 3-Dimensional Matching. Those results are obtained by a simple local"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1304.1424","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1304.1424","created_at":"2026-05-18T03:15:34.229954+00:00"},{"alias_kind":"arxiv_version","alias_value":"1304.1424v2","created_at":"2026-05-18T03:15:34.229954+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1304.1424","created_at":"2026-05-18T03:15:34.229954+00:00"},{"alias_kind":"pith_short_12","alias_value":"DC55LTB633DQ","created_at":"2026-05-18T12:27:40.988391+00:00"},{"alias_kind":"pith_short_16","alias_value":"DC55LTB633DQLGY4","created_at":"2026-05-18T12:27:40.988391+00:00"},{"alias_kind":"pith_short_8","alias_value":"DC55LTB6","created_at":"2026-05-18T12:27:40.988391+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/DC55LTB633DQLGY4EYE3WVLMF7","json":"https://pith.science/pith/DC55LTB633DQLGY4EYE3WVLMF7.json","graph_json":"https://pith.science/api/pith-number/DC55LTB633DQLGY4EYE3WVLMF7/graph.json","events_json":"https://pith.science/api/pith-number/DC55LTB633DQLGY4EYE3WVLMF7/events.json","paper":"https://pith.science/paper/DC55LTB6"},"agent_actions":{"view_html":"https://pith.science/pith/DC55LTB633DQLGY4EYE3WVLMF7","download_json":"https://pith.science/pith/DC55LTB633DQLGY4EYE3WVLMF7.json","view_paper":"https://pith.science/paper/DC55LTB6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1304.1424&json=true","fetch_graph":"https://pith.science/api/pith-number/DC55LTB633DQLGY4EYE3WVLMF7/graph.json","fetch_events":"https://pith.science/api/pith-number/DC55LTB633DQLGY4EYE3WVLMF7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DC55LTB633DQLGY4EYE3WVLMF7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DC55LTB633DQLGY4EYE3WVLMF7/action/storage_attestation","attest_author":"https://pith.science/pith/DC55LTB633DQLGY4EYE3WVLMF7/action/author_attestation","sign_citation":"https://pith.science/pith/DC55LTB633DQLGY4EYE3WVLMF7/action/citation_signature","submit_replication":"https://pith.science/pith/DC55LTB633DQLGY4EYE3WVLMF7/action/replication_record"}},"created_at":"2026-05-18T03:15:34.229954+00:00","updated_at":"2026-05-18T03:15:34.229954+00:00"}