{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:KKWVCTKP2KXFGJZQ4U4KCL3IL2","short_pith_number":"pith:KKWVCTKP","schema_version":"1.0","canonical_sha256":"52ad514d4fd2ae532730e538a12f685ea7e3ebcacd8569a1387e6ca236190e94","source":{"kind":"arxiv","id":"1601.05775","version":2},"attestation_state":"computed","paper":{"title":"Local Network Community Detection with Continuous Optimization of Conductance and Weighted Kernel K-Means","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.SI","authors_text":"Elena Marchiori, Twan van Laarhoven","submitted_at":"2016-01-21T20:36:59Z","abstract_excerpt":"Local network community detection is the task of finding a single community of nodes concentrated around few given seed nodes in a localized way. Conductance is a popular objective function used in many algorithms for local community detection. This paper studies a continuous relaxation of conductance. We show that continuous optimization of this objective still leads to discrete communities. We investigate the relation of conductance with weighted kernel k-means for a single community, which leads to the introduction of a new objective function, $\\sigma$-conductance. Conductance is obtained b"},"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":"1601.05775","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2016-01-21T20:36:59Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"f017de8775d369e211c31d955207c5ea85766543ef8f0b2a350c590b33c8baa0","abstract_canon_sha256":"8f6f502084b0a6346a6fe65258198525d31c96c2ea98600edd9b71c416509625"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:08:35.571425Z","signature_b64":"KrTdVKILPPP8otkwYzGMWTwYpb+h5nsGkQxBsG8Fd5op7ACG0apOjNcCQVYzXplUem748vPH/dQ671iscO2XDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"52ad514d4fd2ae532730e538a12f685ea7e3ebcacd8569a1387e6ca236190e94","last_reissued_at":"2026-05-18T01:08:35.570806Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:08:35.570806Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Local Network Community Detection with Continuous Optimization of Conductance and Weighted Kernel K-Means","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.SI","authors_text":"Elena Marchiori, Twan van Laarhoven","submitted_at":"2016-01-21T20:36:59Z","abstract_excerpt":"Local network community detection is the task of finding a single community of nodes concentrated around few given seed nodes in a localized way. Conductance is a popular objective function used in many algorithms for local community detection. This paper studies a continuous relaxation of conductance. We show that continuous optimization of this objective still leads to discrete communities. We investigate the relation of conductance with weighted kernel k-means for a single community, which leads to the introduction of a new objective function, $\\sigma$-conductance. Conductance is obtained b"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1601.05775","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":"1601.05775","created_at":"2026-05-18T01:08:35.570884+00:00"},{"alias_kind":"arxiv_version","alias_value":"1601.05775v2","created_at":"2026-05-18T01:08:35.570884+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1601.05775","created_at":"2026-05-18T01:08:35.570884+00:00"},{"alias_kind":"pith_short_12","alias_value":"KKWVCTKP2KXF","created_at":"2026-05-18T12:30:25.849896+00:00"},{"alias_kind":"pith_short_16","alias_value":"KKWVCTKP2KXFGJZQ","created_at":"2026-05-18T12:30:25.849896+00:00"},{"alias_kind":"pith_short_8","alias_value":"KKWVCTKP","created_at":"2026-05-18T12:30:25.849896+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/KKWVCTKP2KXFGJZQ4U4KCL3IL2","json":"https://pith.science/pith/KKWVCTKP2KXFGJZQ4U4KCL3IL2.json","graph_json":"https://pith.science/api/pith-number/KKWVCTKP2KXFGJZQ4U4KCL3IL2/graph.json","events_json":"https://pith.science/api/pith-number/KKWVCTKP2KXFGJZQ4U4KCL3IL2/events.json","paper":"https://pith.science/paper/KKWVCTKP"},"agent_actions":{"view_html":"https://pith.science/pith/KKWVCTKP2KXFGJZQ4U4KCL3IL2","download_json":"https://pith.science/pith/KKWVCTKP2KXFGJZQ4U4KCL3IL2.json","view_paper":"https://pith.science/paper/KKWVCTKP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1601.05775&json=true","fetch_graph":"https://pith.science/api/pith-number/KKWVCTKP2KXFGJZQ4U4KCL3IL2/graph.json","fetch_events":"https://pith.science/api/pith-number/KKWVCTKP2KXFGJZQ4U4KCL3IL2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KKWVCTKP2KXFGJZQ4U4KCL3IL2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KKWVCTKP2KXFGJZQ4U4KCL3IL2/action/storage_attestation","attest_author":"https://pith.science/pith/KKWVCTKP2KXFGJZQ4U4KCL3IL2/action/author_attestation","sign_citation":"https://pith.science/pith/KKWVCTKP2KXFGJZQ4U4KCL3IL2/action/citation_signature","submit_replication":"https://pith.science/pith/KKWVCTKP2KXFGJZQ4U4KCL3IL2/action/replication_record"}},"created_at":"2026-05-18T01:08:35.570884+00:00","updated_at":"2026-05-18T01:08:35.570884+00:00"}