{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2011:JU6DQKMSQVOWVUBLQB3EP27NU6","short_pith_number":"pith:JU6DQKMS","schema_version":"1.0","canonical_sha256":"4d3c382992855d6ad02b807647ebeda7b0a871acf479e7c289b78e0d201727c8","source":{"kind":"arxiv","id":"1112.2319","version":1},"attestation_state":"computed","paper":{"title":"Graph Construction for Learning with Unbalanced Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ML","authors_text":"Jing Qian, Manqi Zhao, Venkatesh Saligrama","submitted_at":"2011-12-11T04:25:29Z","abstract_excerpt":"Unbalanced data arises in many learning tasks such as clustering of multi-class data, hierarchical divisive clustering and semisupervised learning. Graph-based approaches are popular tools for these problems. Graph construction is an important aspect of graph-based learning. We show that graph-based algorithms can fail for unbalanced data for many popular graphs such as k-NN, \\epsilon-neighborhood and full-RBF graphs. We propose a novel graph construction technique that encodes global statistical information into node degrees through a ranking scheme. The rank of a data sample is an estimate o"},"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":"1112.2319","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2011-12-11T04:25:29Z","cross_cats_sorted":[],"title_canon_sha256":"08ec8eb598ebba09b113d5526b997ea96ea283caafd39416d3cd203088e9773e","abstract_canon_sha256":"cb2f466babed7d25a635d9c941a18c8f55b50a6daad75913c1c945cab7a2098d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:06:34.822982Z","signature_b64":"2GqlmAO/Qj+B7klxUwV0ebFFgLFQyotfkw16jNTDaYWkAztQfpPgBO5skae+pASVLpIUhQS+QcLlhZ2nGkfFBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4d3c382992855d6ad02b807647ebeda7b0a871acf479e7c289b78e0d201727c8","last_reissued_at":"2026-05-18T04:06:34.822246Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:06:34.822246Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Graph Construction for Learning with Unbalanced Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ML","authors_text":"Jing Qian, Manqi Zhao, Venkatesh Saligrama","submitted_at":"2011-12-11T04:25:29Z","abstract_excerpt":"Unbalanced data arises in many learning tasks such as clustering of multi-class data, hierarchical divisive clustering and semisupervised learning. Graph-based approaches are popular tools for these problems. Graph construction is an important aspect of graph-based learning. We show that graph-based algorithms can fail for unbalanced data for many popular graphs such as k-NN, \\epsilon-neighborhood and full-RBF graphs. We propose a novel graph construction technique that encodes global statistical information into node degrees through a ranking scheme. The rank of a data sample is an estimate o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1112.2319","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":"1112.2319","created_at":"2026-05-18T04:06:34.822374+00:00"},{"alias_kind":"arxiv_version","alias_value":"1112.2319v1","created_at":"2026-05-18T04:06:34.822374+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1112.2319","created_at":"2026-05-18T04:06:34.822374+00:00"},{"alias_kind":"pith_short_12","alias_value":"JU6DQKMSQVOW","created_at":"2026-05-18T12:26:32.869790+00:00"},{"alias_kind":"pith_short_16","alias_value":"JU6DQKMSQVOWVUBL","created_at":"2026-05-18T12:26:32.869790+00:00"},{"alias_kind":"pith_short_8","alias_value":"JU6DQKMS","created_at":"2026-05-18T12:26:32.869790+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/JU6DQKMSQVOWVUBLQB3EP27NU6","json":"https://pith.science/pith/JU6DQKMSQVOWVUBLQB3EP27NU6.json","graph_json":"https://pith.science/api/pith-number/JU6DQKMSQVOWVUBLQB3EP27NU6/graph.json","events_json":"https://pith.science/api/pith-number/JU6DQKMSQVOWVUBLQB3EP27NU6/events.json","paper":"https://pith.science/paper/JU6DQKMS"},"agent_actions":{"view_html":"https://pith.science/pith/JU6DQKMSQVOWVUBLQB3EP27NU6","download_json":"https://pith.science/pith/JU6DQKMSQVOWVUBLQB3EP27NU6.json","view_paper":"https://pith.science/paper/JU6DQKMS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1112.2319&json=true","fetch_graph":"https://pith.science/api/pith-number/JU6DQKMSQVOWVUBLQB3EP27NU6/graph.json","fetch_events":"https://pith.science/api/pith-number/JU6DQKMSQVOWVUBLQB3EP27NU6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JU6DQKMSQVOWVUBLQB3EP27NU6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JU6DQKMSQVOWVUBLQB3EP27NU6/action/storage_attestation","attest_author":"https://pith.science/pith/JU6DQKMSQVOWVUBLQB3EP27NU6/action/author_attestation","sign_citation":"https://pith.science/pith/JU6DQKMSQVOWVUBLQB3EP27NU6/action/citation_signature","submit_replication":"https://pith.science/pith/JU6DQKMSQVOWVUBLQB3EP27NU6/action/replication_record"}},"created_at":"2026-05-18T04:06:34.822374+00:00","updated_at":"2026-05-18T04:06:34.822374+00:00"}