{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:RXSUK5O5PVYZXJZCNV6UWYZL5S","short_pith_number":"pith:RXSUK5O5","schema_version":"1.0","canonical_sha256":"8de54575dd7d719ba7226d7d4b632beca95d65585b9a1b16d5e3b9bdd0fc1f9f","source":{"kind":"arxiv","id":"1809.01415","version":1},"attestation_state":"computed","paper":{"title":"Exploration of Bi-Level PageRank Algorithm for Power Flow Analysis Using Graph Database","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DB","math.NA","math.OC"],"primary_cat":"cs.DC","authors_text":"Chen Yuan, Guangyi Liu, Kewen Liu, Renchang Dai, Yi Lu, Zhiwei Wang","submitted_at":"2018-09-05T09:59:18Z","abstract_excerpt":"Compared with traditional relational database, graph database, GDB, is a natural expression of most real-world systems. Each node in the GDB is not only a storage unit, but also a logic operation unit to implement local computation in parallel. This paper firstly explores the feasibility of power system modeling using GDB. Then a brief introduction of the PageRank algorithm and the feasibility analysis of its application in GDB are presented. Then the proposed GDB based bilevel PageRank algorithm is developed from PageRank algorithm and Gauss Seidel methodology realize high performance paralle"},"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":"1809.01415","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2018-09-05T09:59:18Z","cross_cats_sorted":["cs.DB","math.NA","math.OC"],"title_canon_sha256":"2da04c87fde33e59f730af27d48d939d9d7346cef64410cf6ea5fe69256b6a33","abstract_canon_sha256":"8cfc52c63952e6354c743ad922aa4d8041efaa846b899346a7d66af3cfb7a77f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:06:27.714792Z","signature_b64":"A5tBLynUUKD4mzP3SEK0+qdKVIL//yxnQ5wpWOiSYG8lG/sGD5fI+ux33353lQJlZTn37YvxlV1dPWGf4pPLBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8de54575dd7d719ba7226d7d4b632beca95d65585b9a1b16d5e3b9bdd0fc1f9f","last_reissued_at":"2026-05-18T00:06:27.714153Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:06:27.714153Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Exploration of Bi-Level PageRank Algorithm for Power Flow Analysis Using Graph Database","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DB","math.NA","math.OC"],"primary_cat":"cs.DC","authors_text":"Chen Yuan, Guangyi Liu, Kewen Liu, Renchang Dai, Yi Lu, Zhiwei Wang","submitted_at":"2018-09-05T09:59:18Z","abstract_excerpt":"Compared with traditional relational database, graph database, GDB, is a natural expression of most real-world systems. Each node in the GDB is not only a storage unit, but also a logic operation unit to implement local computation in parallel. This paper firstly explores the feasibility of power system modeling using GDB. Then a brief introduction of the PageRank algorithm and the feasibility analysis of its application in GDB are presented. Then the proposed GDB based bilevel PageRank algorithm is developed from PageRank algorithm and Gauss Seidel methodology realize high performance paralle"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.01415","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1809.01415","created_at":"2026-05-18T00:06:27.714248+00:00"},{"alias_kind":"arxiv_version","alias_value":"1809.01415v1","created_at":"2026-05-18T00:06:27.714248+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.01415","created_at":"2026-05-18T00:06:27.714248+00:00"},{"alias_kind":"pith_short_12","alias_value":"RXSUK5O5PVYZ","created_at":"2026-05-18T12:32:50.500415+00:00"},{"alias_kind":"pith_short_16","alias_value":"RXSUK5O5PVYZXJZC","created_at":"2026-05-18T12:32:50.500415+00:00"},{"alias_kind":"pith_short_8","alias_value":"RXSUK5O5","created_at":"2026-05-18T12:32:50.500415+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/RXSUK5O5PVYZXJZCNV6UWYZL5S","json":"https://pith.science/pith/RXSUK5O5PVYZXJZCNV6UWYZL5S.json","graph_json":"https://pith.science/api/pith-number/RXSUK5O5PVYZXJZCNV6UWYZL5S/graph.json","events_json":"https://pith.science/api/pith-number/RXSUK5O5PVYZXJZCNV6UWYZL5S/events.json","paper":"https://pith.science/paper/RXSUK5O5"},"agent_actions":{"view_html":"https://pith.science/pith/RXSUK5O5PVYZXJZCNV6UWYZL5S","download_json":"https://pith.science/pith/RXSUK5O5PVYZXJZCNV6UWYZL5S.json","view_paper":"https://pith.science/paper/RXSUK5O5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1809.01415&json=true","fetch_graph":"https://pith.science/api/pith-number/RXSUK5O5PVYZXJZCNV6UWYZL5S/graph.json","fetch_events":"https://pith.science/api/pith-number/RXSUK5O5PVYZXJZCNV6UWYZL5S/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RXSUK5O5PVYZXJZCNV6UWYZL5S/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RXSUK5O5PVYZXJZCNV6UWYZL5S/action/storage_attestation","attest_author":"https://pith.science/pith/RXSUK5O5PVYZXJZCNV6UWYZL5S/action/author_attestation","sign_citation":"https://pith.science/pith/RXSUK5O5PVYZXJZCNV6UWYZL5S/action/citation_signature","submit_replication":"https://pith.science/pith/RXSUK5O5PVYZXJZCNV6UWYZL5S/action/replication_record"}},"created_at":"2026-05-18T00:06:27.714248+00:00","updated_at":"2026-05-18T00:06:27.714248+00:00"}