{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:GGL2FRZCGF3YGF75537FMKEK6Q","short_pith_number":"pith:GGL2FRZC","schema_version":"1.0","canonical_sha256":"3197a2c72231778317fdeefe56288af43bfd3d6fe99dba2986e0086511cf6ea3","source":{"kind":"arxiv","id":"1711.05857","version":2},"attestation_state":"computed","paper":{"title":"An Optimal and Progressive Approach to Online Search of Top-k Influential Communities","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SI"],"primary_cat":"cs.DB","authors_text":"Fei Bi, Lijun Chang, Wenjie Zhang, Xuemin Lin","submitted_at":"2017-11-16T00:12:25Z","abstract_excerpt":"Community search over large graphs is a fundamental problem in graph analysis. Recent studies propose to compute top-k influential communities, where each reported community not only is a cohesive subgraph but also has a high influence value. The existing approaches to the problem of top-k influential community search can be categorized as index-based algorithms and online search algorithms without indexes. The index-based algorithms, although being very efficient in conducting community searches, need to pre-compute a special-purpose index and only work for one built-in vertex weight vector. "},"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":"1711.05857","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DB","submitted_at":"2017-11-16T00:12:25Z","cross_cats_sorted":["cs.SI"],"title_canon_sha256":"52113aca9ac7d29af026595b5d0228610b0a48ddde2e680713b6e5dedd93af6f","abstract_canon_sha256":"8913ebb997033fa17a2c69f86566752113ef10dc88b31d94c344dada6a050be7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:28:01.715780Z","signature_b64":"wLqr+YLIOxq5F0c+v0t2efNyLK0bl/DC9O+juDXO0L++prJPe9hMDNjhciLHbki7Md3SdY08uAn1/5YpgqQwBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3197a2c72231778317fdeefe56288af43bfd3d6fe99dba2986e0086511cf6ea3","last_reissued_at":"2026-05-18T00:28:01.715112Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:28:01.715112Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"An Optimal and Progressive Approach to Online Search of Top-k Influential Communities","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SI"],"primary_cat":"cs.DB","authors_text":"Fei Bi, Lijun Chang, Wenjie Zhang, Xuemin Lin","submitted_at":"2017-11-16T00:12:25Z","abstract_excerpt":"Community search over large graphs is a fundamental problem in graph analysis. Recent studies propose to compute top-k influential communities, where each reported community not only is a cohesive subgraph but also has a high influence value. The existing approaches to the problem of top-k influential community search can be categorized as index-based algorithms and online search algorithms without indexes. The index-based algorithms, although being very efficient in conducting community searches, need to pre-compute a special-purpose index and only work for one built-in vertex weight vector. "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.05857","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":"1711.05857","created_at":"2026-05-18T00:28:01.715197+00:00"},{"alias_kind":"arxiv_version","alias_value":"1711.05857v2","created_at":"2026-05-18T00:28:01.715197+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.05857","created_at":"2026-05-18T00:28:01.715197+00:00"},{"alias_kind":"pith_short_12","alias_value":"GGL2FRZCGF3Y","created_at":"2026-05-18T12:31:15.632608+00:00"},{"alias_kind":"pith_short_16","alias_value":"GGL2FRZCGF3YGF75","created_at":"2026-05-18T12:31:15.632608+00:00"},{"alias_kind":"pith_short_8","alias_value":"GGL2FRZC","created_at":"2026-05-18T12:31:15.632608+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2401.12895","citing_title":"Skyline Community Search over Edge-Attributed Bipartite Graphs","ref_index":40,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/GGL2FRZCGF3YGF75537FMKEK6Q","json":"https://pith.science/pith/GGL2FRZCGF3YGF75537FMKEK6Q.json","graph_json":"https://pith.science/api/pith-number/GGL2FRZCGF3YGF75537FMKEK6Q/graph.json","events_json":"https://pith.science/api/pith-number/GGL2FRZCGF3YGF75537FMKEK6Q/events.json","paper":"https://pith.science/paper/GGL2FRZC"},"agent_actions":{"view_html":"https://pith.science/pith/GGL2FRZCGF3YGF75537FMKEK6Q","download_json":"https://pith.science/pith/GGL2FRZCGF3YGF75537FMKEK6Q.json","view_paper":"https://pith.science/paper/GGL2FRZC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1711.05857&json=true","fetch_graph":"https://pith.science/api/pith-number/GGL2FRZCGF3YGF75537FMKEK6Q/graph.json","fetch_events":"https://pith.science/api/pith-number/GGL2FRZCGF3YGF75537FMKEK6Q/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/GGL2FRZCGF3YGF75537FMKEK6Q/action/timestamp_anchor","attest_storage":"https://pith.science/pith/GGL2FRZCGF3YGF75537FMKEK6Q/action/storage_attestation","attest_author":"https://pith.science/pith/GGL2FRZCGF3YGF75537FMKEK6Q/action/author_attestation","sign_citation":"https://pith.science/pith/GGL2FRZCGF3YGF75537FMKEK6Q/action/citation_signature","submit_replication":"https://pith.science/pith/GGL2FRZCGF3YGF75537FMKEK6Q/action/replication_record"}},"created_at":"2026-05-18T00:28:01.715197+00:00","updated_at":"2026-05-18T00:28:01.715197+00:00"}