{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:DRPGOA7QDOWBXKGMRP22PAZ32O","short_pith_number":"pith:DRPGOA7Q","schema_version":"1.0","canonical_sha256":"1c5e6703f01bac1ba8cc8bf5a7833bd388d681aa186c79a4684172fe4dedcd22","source":{"kind":"arxiv","id":"1404.1864","version":3},"attestation_state":"computed","paper":{"title":"Sublinear algorithms for local graph centrality estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR","cs.SI"],"primary_cat":"cs.DS","authors_text":"Enoch Peserico, Luca Pretto, Marco Bressan","submitted_at":"2014-04-07T17:57:33Z","abstract_excerpt":"We study the complexity of local graph centrality estimation, with the goal of approximating the centrality score of a given target node while exploring only a sublinear number of nodes/arcs of the graph and performing a sublinear number of elementary operations. We develop a technique, that we apply to the PageRank and Heat Kernel centralities, for building a low-variance score estimator through a local exploration of the graph. We obtain an algorithm that, given any node in any graph of $m$ arcs, with probability $(1-\\delta)$ computes a multiplicative $(1\\pm\\epsilon)$-approximation of its sc"},"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":"1404.1864","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2014-04-07T17:57:33Z","cross_cats_sorted":["cs.IR","cs.SI"],"title_canon_sha256":"5409b8524e39bc4fb24a4c1d15854432172fc6f42d818bb1b9ede2c4eb5c19ed","abstract_canon_sha256":"d89b21e3a6b10e5f5917b5e5d8f251d0da7b97b3bd57acfe4a2f6582bbb29b73"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:08:58.291996Z","signature_b64":"DlJisbdLpJBmFzT1UMl5ZwfHewFVL+6oA2KZkG9YBzYohle6dRvESFbVO4eUr4E7QLDpO4ZTLGn4WUieI6/0Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1c5e6703f01bac1ba8cc8bf5a7833bd388d681aa186c79a4684172fe4dedcd22","last_reissued_at":"2026-05-18T00:08:58.291364Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:08:58.291364Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Sublinear algorithms for local graph centrality estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR","cs.SI"],"primary_cat":"cs.DS","authors_text":"Enoch Peserico, Luca Pretto, Marco Bressan","submitted_at":"2014-04-07T17:57:33Z","abstract_excerpt":"We study the complexity of local graph centrality estimation, with the goal of approximating the centrality score of a given target node while exploring only a sublinear number of nodes/arcs of the graph and performing a sublinear number of elementary operations. We develop a technique, that we apply to the PageRank and Heat Kernel centralities, for building a low-variance score estimator through a local exploration of the graph. We obtain an algorithm that, given any node in any graph of $m$ arcs, with probability $(1-\\delta)$ computes a multiplicative $(1\\pm\\epsilon)$-approximation of its sc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1404.1864","kind":"arxiv","version":3},"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":"1404.1864","created_at":"2026-05-18T00:08:58.291448+00:00"},{"alias_kind":"arxiv_version","alias_value":"1404.1864v3","created_at":"2026-05-18T00:08:58.291448+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1404.1864","created_at":"2026-05-18T00:08:58.291448+00:00"},{"alias_kind":"pith_short_12","alias_value":"DRPGOA7QDOWB","created_at":"2026-05-18T12:28:25.294606+00:00"},{"alias_kind":"pith_short_16","alias_value":"DRPGOA7QDOWBXKGM","created_at":"2026-05-18T12:28:25.294606+00:00"},{"alias_kind":"pith_short_8","alias_value":"DRPGOA7Q","created_at":"2026-05-18T12:28:25.294606+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/DRPGOA7QDOWBXKGMRP22PAZ32O","json":"https://pith.science/pith/DRPGOA7QDOWBXKGMRP22PAZ32O.json","graph_json":"https://pith.science/api/pith-number/DRPGOA7QDOWBXKGMRP22PAZ32O/graph.json","events_json":"https://pith.science/api/pith-number/DRPGOA7QDOWBXKGMRP22PAZ32O/events.json","paper":"https://pith.science/paper/DRPGOA7Q"},"agent_actions":{"view_html":"https://pith.science/pith/DRPGOA7QDOWBXKGMRP22PAZ32O","download_json":"https://pith.science/pith/DRPGOA7QDOWBXKGMRP22PAZ32O.json","view_paper":"https://pith.science/paper/DRPGOA7Q","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1404.1864&json=true","fetch_graph":"https://pith.science/api/pith-number/DRPGOA7QDOWBXKGMRP22PAZ32O/graph.json","fetch_events":"https://pith.science/api/pith-number/DRPGOA7QDOWBXKGMRP22PAZ32O/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DRPGOA7QDOWBXKGMRP22PAZ32O/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DRPGOA7QDOWBXKGMRP22PAZ32O/action/storage_attestation","attest_author":"https://pith.science/pith/DRPGOA7QDOWBXKGMRP22PAZ32O/action/author_attestation","sign_citation":"https://pith.science/pith/DRPGOA7QDOWBXKGMRP22PAZ32O/action/citation_signature","submit_replication":"https://pith.science/pith/DRPGOA7QDOWBXKGMRP22PAZ32O/action/replication_record"}},"created_at":"2026-05-18T00:08:58.291448+00:00","updated_at":"2026-05-18T00:08:58.291448+00:00"}