{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:EHE2XRCLJGPX76NTEYVYAI2Q3P","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":"6c24e8e2367e58cd71558cc99c8516fe0099b07e0931c33019eb5d5c457ad462","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2019-02-15T05:29:34Z","title_canon_sha256":"e7a1b7d265dec1b583902ad7cd7b692bdd0181c6e83d70dd95ca6b2eb44282d7"},"schema_version":"1.0","source":{"id":"1902.06684","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.06684","created_at":"2026-05-17T23:53:44Z"},{"alias_kind":"arxiv_version","alias_value":"1902.06684v1","created_at":"2026-05-17T23:53:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.06684","created_at":"2026-05-17T23:53:44Z"},{"alias_kind":"pith_short_12","alias_value":"EHE2XRCLJGPX","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"EHE2XRCLJGPX76NT","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"EHE2XRCL","created_at":"2026-05-18T12:33:15Z"}],"graph_snapshots":[{"event_id":"sha256:0d8c2780031181e22628ae445449d5cdf2869df4308b90c731b8056d6ead3d9b","target":"graph","created_at":"2026-05-17T23:53:44Z","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"},"paper":{"abstract_excerpt":"The topological information is essential for studying the relationship between nodes in a network. Recently, Network Representation Learning (NRL), which projects a network into a low-dimensional vector space, has been shown their advantages in analyzing large-scale networks. However, most existing NRL methods are designed to preserve the local topology of a network, they fail to capture the global topology. To tackle this issue, we propose a new NRL framework, named HSRL, to help existing NRL methods capture both the local and global topological information of a network. Specifically, HSRL re","authors_text":"Chengbin Hou, Guoji Fu, Xin Yao","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2019-02-15T05:29:34Z","title":"Learning Topological Representation for Networks via Hierarchical Sampling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.06684","kind":"arxiv","version":1},"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":"sha256:552023a769ec5bbd64e6bbeb3f2880cf5216ced71edc916bc84ce5ff17b19e98","target":"record","created_at":"2026-05-17T23:53:44Z","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":"6c24e8e2367e58cd71558cc99c8516fe0099b07e0931c33019eb5d5c457ad462","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2019-02-15T05:29:34Z","title_canon_sha256":"e7a1b7d265dec1b583902ad7cd7b692bdd0181c6e83d70dd95ca6b2eb44282d7"},"schema_version":"1.0","source":{"id":"1902.06684","kind":"arxiv","version":1}},"canonical_sha256":"21c9abc44b499f7ff9b3262b802350dbedab4a9dfd2de97e7149e1a126e0c101","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"21c9abc44b499f7ff9b3262b802350dbedab4a9dfd2de97e7149e1a126e0c101","first_computed_at":"2026-05-17T23:53:44.811017Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:53:44.811017Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"c53sF4I4+h6mbDuZ3/MDfIyBpnXhFcdhar87nYWQtU1/ROKYQx2EPpMmfzQGRwoRMaxvsVJp/KhU7+I8QKg+Cw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:53:44.811417Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.06684","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:552023a769ec5bbd64e6bbeb3f2880cf5216ced71edc916bc84ce5ff17b19e98","sha256:0d8c2780031181e22628ae445449d5cdf2869df4308b90c731b8056d6ead3d9b"],"state_sha256":"86c80279387cbf345be9295a4d0cde36d5d80fef91d37e365b4314313f7ffe6d"}