{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:JMJT7J3P2IPM4H5Z763NJJ7GE6","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"d832bd537e59080becaf33dcecde5a90898ca637275cda85494b941e84caee0c","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2021-10-31T10:49:21Z","title_canon_sha256":"667ec291cd775f0ef438263faa629a49b2bcd6aae49cdd1564e587e080ac7f3a"},"schema_version":"1.0","source":{"id":"2111.00463","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.00463","created_at":"2026-07-05T04:24:23Z"},{"alias_kind":"arxiv_version","alias_value":"2111.00463v2","created_at":"2026-07-05T04:24:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.00463","created_at":"2026-07-05T04:24:23Z"},{"alias_kind":"pith_short_12","alias_value":"JMJT7J3P2IPM","created_at":"2026-07-05T04:24:23Z"},{"alias_kind":"pith_short_16","alias_value":"JMJT7J3P2IPM4H5Z","created_at":"2026-07-05T04:24:23Z"},{"alias_kind":"pith_short_8","alias_value":"JMJT7J3P","created_at":"2026-07-05T04:24:23Z"}],"graph_snapshots":[{"event_id":"sha256:8c96702a824792c6a6e352095f9e2f7a376ac368294705a3998c2e7640e9682c","target":"graph","created_at":"2026-07-05T04:24:23Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2111.00463/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Finding influential users in social networks is a fundamental problem with many possible useful applications. Viewing the social network as a graph, the influence of a set of users can be measured by the number of neighbors located within a given number of hops in the network, where each hop marks a step of influence diffusion. In this paper, we reduce the problem of IM to a budget-constrained d-hop dominating set problem (kdDSP). We propose a unified machine learning (ML) framework, FastCover, to solve kdDSP by learning an efficient greedy strategy in an unsupervised way. As one critical comp","authors_text":"Fangqi Li, Guihai Chen, Runbo Ni, Xiaofeng Gao, Xueyan Li","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2021-10-31T10:49:21Z","title":"FastCover: An Unsupervised Learning Framework for Multi-Hop Influence Maximization in Social Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.00463","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:973bd1864a8e1c18b29c40702434debd87637b7bcc6c8c8fed30604c722e0577","target":"record","created_at":"2026-07-05T04:24:23Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"d832bd537e59080becaf33dcecde5a90898ca637275cda85494b941e84caee0c","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2021-10-31T10:49:21Z","title_canon_sha256":"667ec291cd775f0ef438263faa629a49b2bcd6aae49cdd1564e587e080ac7f3a"},"schema_version":"1.0","source":{"id":"2111.00463","kind":"arxiv","version":2}},"canonical_sha256":"4b133fa76fd21ece1fb9ffb6d4a7e627b06a0745f6f1019088cca0e1d3834ecc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4b133fa76fd21ece1fb9ffb6d4a7e627b06a0745f6f1019088cca0e1d3834ecc","first_computed_at":"2026-07-05T04:24:23.457163Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:24:23.457163Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XIbDYOjObaLx1xshpXHpatMGCJ6bnXm4fmcWlsra1q1mAuImW7TCeyts0/DmVPh+w6lXk7TtXcOYRMpJqn83Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:24:23.457575Z","signed_message":"canonical_sha256_bytes"},"source_id":"2111.00463","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:973bd1864a8e1c18b29c40702434debd87637b7bcc6c8c8fed30604c722e0577","sha256:8c96702a824792c6a6e352095f9e2f7a376ac368294705a3998c2e7640e9682c"],"state_sha256":"4d303c1c89a82e7f58b2614d15ed56e894a193f2277661c2a3c9fca45862c121"}