{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:3COD7TFRX5MR5DTORB2J4RACUJ","short_pith_number":"pith:3COD7TFR","schema_version":"1.0","canonical_sha256":"d89c3fccb1bf591e8e6e88749e4402a24daf8f9899db9aed12c7d2ece6a3b073","source":{"kind":"arxiv","id":"1605.03871","version":2},"attestation_state":"computed","paper":{"title":"Adapting the Bron-Kerbosch Algorithm for Enumerating Maximal Cliques in Temporal Graphs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CC","cs.SI"],"primary_cat":"cs.DS","authors_text":"Anne-Sophie Himmel, Hendrik Molter, Manuel Sorge, Rolf Niedermeier","submitted_at":"2016-05-12T15:59:48Z","abstract_excerpt":"Dynamics of interactions play an increasingly important role in the analysis of complex networks. A modeling framework to capture this are temporal graphs which consist of a set of vertices (entities in the network) and a set of time-stamped binary interactions between the vertices. We focus on enumerating delta-cliques, an extension of the concept of cliques to temporal graphs: for a given time period delta, a delta-clique in a temporal graph is a set of vertices and a time interval such that all vertices interact with each other at least after every delta time steps within the time interval."},"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":"1605.03871","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2016-05-12T15:59:48Z","cross_cats_sorted":["cs.CC","cs.SI"],"title_canon_sha256":"1214491f58bdf344fae8bb1850a3689393c6873365c123d3ec3ac7e1bc8379e1","abstract_canon_sha256":"41e66ec3775bc2c09bf8a4dae2bee45166d9b57972f82da6e86e3636c8072fd0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:45:16.113075Z","signature_b64":"VVWv4YO2AiqTXCLZB7qc2e9bmhWdHDiG0uxTjHcYXxJsXPNHzDufMxud21B3CxHeMQyXQXRjwjBr520cJfr0CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d89c3fccb1bf591e8e6e88749e4402a24daf8f9899db9aed12c7d2ece6a3b073","last_reissued_at":"2026-05-18T00:45:16.112374Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:45:16.112374Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Adapting the Bron-Kerbosch Algorithm for Enumerating Maximal Cliques in Temporal Graphs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CC","cs.SI"],"primary_cat":"cs.DS","authors_text":"Anne-Sophie Himmel, Hendrik Molter, Manuel Sorge, Rolf Niedermeier","submitted_at":"2016-05-12T15:59:48Z","abstract_excerpt":"Dynamics of interactions play an increasingly important role in the analysis of complex networks. A modeling framework to capture this are temporal graphs which consist of a set of vertices (entities in the network) and a set of time-stamped binary interactions between the vertices. We focus on enumerating delta-cliques, an extension of the concept of cliques to temporal graphs: for a given time period delta, a delta-clique in a temporal graph is a set of vertices and a time interval such that all vertices interact with each other at least after every delta time steps within the time interval."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1605.03871","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":"1605.03871","created_at":"2026-05-18T00:45:16.112486+00:00"},{"alias_kind":"arxiv_version","alias_value":"1605.03871v2","created_at":"2026-05-18T00:45:16.112486+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1605.03871","created_at":"2026-05-18T00:45:16.112486+00:00"},{"alias_kind":"pith_short_12","alias_value":"3COD7TFRX5MR","created_at":"2026-05-18T12:29:55.572404+00:00"},{"alias_kind":"pith_short_16","alias_value":"3COD7TFRX5MR5DTO","created_at":"2026-05-18T12:29:55.572404+00:00"},{"alias_kind":"pith_short_8","alias_value":"3COD7TFR","created_at":"2026-05-18T12:29:55.572404+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/3COD7TFRX5MR5DTORB2J4RACUJ","json":"https://pith.science/pith/3COD7TFRX5MR5DTORB2J4RACUJ.json","graph_json":"https://pith.science/api/pith-number/3COD7TFRX5MR5DTORB2J4RACUJ/graph.json","events_json":"https://pith.science/api/pith-number/3COD7TFRX5MR5DTORB2J4RACUJ/events.json","paper":"https://pith.science/paper/3COD7TFR"},"agent_actions":{"view_html":"https://pith.science/pith/3COD7TFRX5MR5DTORB2J4RACUJ","download_json":"https://pith.science/pith/3COD7TFRX5MR5DTORB2J4RACUJ.json","view_paper":"https://pith.science/paper/3COD7TFR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1605.03871&json=true","fetch_graph":"https://pith.science/api/pith-number/3COD7TFRX5MR5DTORB2J4RACUJ/graph.json","fetch_events":"https://pith.science/api/pith-number/3COD7TFRX5MR5DTORB2J4RACUJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3COD7TFRX5MR5DTORB2J4RACUJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3COD7TFRX5MR5DTORB2J4RACUJ/action/storage_attestation","attest_author":"https://pith.science/pith/3COD7TFRX5MR5DTORB2J4RACUJ/action/author_attestation","sign_citation":"https://pith.science/pith/3COD7TFRX5MR5DTORB2J4RACUJ/action/citation_signature","submit_replication":"https://pith.science/pith/3COD7TFRX5MR5DTORB2J4RACUJ/action/replication_record"}},"created_at":"2026-05-18T00:45:16.112486+00:00","updated_at":"2026-05-18T00:45:16.112486+00:00"}