{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:MNKLSITKD3RQ7FJI6D6YGI4JWA","short_pith_number":"pith:MNKLSITK","schema_version":"1.0","canonical_sha256":"6354b9226a1ee30f9528f0fd832389b003733214a1eb9acdf5ff3b6b31e9854c","source":{"kind":"arxiv","id":"1411.0064","version":1},"attestation_state":"computed","paper":{"title":"ALID: Scalable Dominant Cluster Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"Jian Pei, Lingyang Chu, Qingming Huang, Shuhui Wang, Siyuan Liu","submitted_at":"2014-11-01T04:13:59Z","abstract_excerpt":"Detecting dominant clusters is important in many analytic applications. The state-of-the-art methods find dense subgraphs on the affinity graph as the dominant clusters. However, the time and space complexity of those methods are dominated by the construction of the affinity graph, which is quadratic with respect to the number of data points, and thus impractical on large data sets. To tackle the challenge, in this paper, we apply Evolutionary Game Theory (EGT) and develop a scalable algorithm, Approximate Localized Infection Immunization Dynamics (ALID). The major idea is to perform Localized"},"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":"1411.0064","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2014-11-01T04:13:59Z","cross_cats_sorted":[],"title_canon_sha256":"d7d0932a80052962d822ac2df1afaa6730494c303676bbe3ff3d06b2ba9bb67e","abstract_canon_sha256":"4cee4a9f4059cb560b2a79f14d1160e88dae289241874aefa4e5536bff7370f7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:38:52.624217Z","signature_b64":"F6khRD0uvTRXyBGmhtIxBkIQKAuN7beRhJY+o6rChPHFO20XhoQjp/qnQN5RIZbxMAbpRo7chEeBVz6UWts/Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6354b9226a1ee30f9528f0fd832389b003733214a1eb9acdf5ff3b6b31e9854c","last_reissued_at":"2026-05-18T02:38:52.623845Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:38:52.623845Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"ALID: Scalable Dominant Cluster Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"Jian Pei, Lingyang Chu, Qingming Huang, Shuhui Wang, Siyuan Liu","submitted_at":"2014-11-01T04:13:59Z","abstract_excerpt":"Detecting dominant clusters is important in many analytic applications. The state-of-the-art methods find dense subgraphs on the affinity graph as the dominant clusters. However, the time and space complexity of those methods are dominated by the construction of the affinity graph, which is quadratic with respect to the number of data points, and thus impractical on large data sets. To tackle the challenge, in this paper, we apply Evolutionary Game Theory (EGT) and develop a scalable algorithm, Approximate Localized Infection Immunization Dynamics (ALID). The major idea is to perform Localized"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1411.0064","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":"1411.0064","created_at":"2026-05-18T02:38:52.623898+00:00"},{"alias_kind":"arxiv_version","alias_value":"1411.0064v1","created_at":"2026-05-18T02:38:52.623898+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1411.0064","created_at":"2026-05-18T02:38:52.623898+00:00"},{"alias_kind":"pith_short_12","alias_value":"MNKLSITKD3RQ","created_at":"2026-05-18T12:28:38.356838+00:00"},{"alias_kind":"pith_short_16","alias_value":"MNKLSITKD3RQ7FJI","created_at":"2026-05-18T12:28:38.356838+00:00"},{"alias_kind":"pith_short_8","alias_value":"MNKLSITK","created_at":"2026-05-18T12:28:38.356838+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/MNKLSITKD3RQ7FJI6D6YGI4JWA","json":"https://pith.science/pith/MNKLSITKD3RQ7FJI6D6YGI4JWA.json","graph_json":"https://pith.science/api/pith-number/MNKLSITKD3RQ7FJI6D6YGI4JWA/graph.json","events_json":"https://pith.science/api/pith-number/MNKLSITKD3RQ7FJI6D6YGI4JWA/events.json","paper":"https://pith.science/paper/MNKLSITK"},"agent_actions":{"view_html":"https://pith.science/pith/MNKLSITKD3RQ7FJI6D6YGI4JWA","download_json":"https://pith.science/pith/MNKLSITKD3RQ7FJI6D6YGI4JWA.json","view_paper":"https://pith.science/paper/MNKLSITK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1411.0064&json=true","fetch_graph":"https://pith.science/api/pith-number/MNKLSITKD3RQ7FJI6D6YGI4JWA/graph.json","fetch_events":"https://pith.science/api/pith-number/MNKLSITKD3RQ7FJI6D6YGI4JWA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MNKLSITKD3RQ7FJI6D6YGI4JWA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MNKLSITKD3RQ7FJI6D6YGI4JWA/action/storage_attestation","attest_author":"https://pith.science/pith/MNKLSITKD3RQ7FJI6D6YGI4JWA/action/author_attestation","sign_citation":"https://pith.science/pith/MNKLSITKD3RQ7FJI6D6YGI4JWA/action/citation_signature","submit_replication":"https://pith.science/pith/MNKLSITKD3RQ7FJI6D6YGI4JWA/action/replication_record"}},"created_at":"2026-05-18T02:38:52.623898+00:00","updated_at":"2026-05-18T02:38:52.623898+00:00"}