{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:52GJLAVRSHIQFTPQYN3N3M7T7P","short_pith_number":"pith:52GJLAVR","schema_version":"1.0","canonical_sha256":"ee8c9582b191d102cdf0c376ddb3f3fbcd1a71081da8a027f9ba09817d694d6a","source":{"kind":"arxiv","id":"1611.03028","version":3},"attestation_state":"computed","paper":{"title":"Node Embedding via Word Embedding for Network Community Discovery","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.soc-ph","stat.ML"],"primary_cat":"cs.SI","authors_text":"Christy Lin, Prakash Ishwar, Weicong Ding","submitted_at":"2016-11-09T17:59:13Z","abstract_excerpt":"Neural node embeddings have recently emerged as a powerful representation for supervised learning tasks involving graph-structured data. We leverage this recent advance to develop a novel algorithm for unsupervised community discovery in graphs. Through extensive experimental studies on simulated and real-world data, we demonstrate that the proposed approach consistently improves over the current state-of-the-art. Specifically, our approach empirically attains the information-theoretic limits for community recovery under the benchmark Stochastic Block Models for graph generation and exhibits 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":"1611.03028","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2016-11-09T17:59:13Z","cross_cats_sorted":["physics.soc-ph","stat.ML"],"title_canon_sha256":"f6e9965739bb6e53bd2abd0f14802239a62779d9793f46edb63447e9e7a66d38","abstract_canon_sha256":"c07e709b929285025b1ec97a3822b2744403933af7e26f4bf1caa400a4ea2265"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:41:18.132727Z","signature_b64":"5j7+PR6MnFWLwxuuVbJfWApV3+61tWNCZbe1AssHRd7gZSyZR3eGX9Jqyi+E8IhAwb6eJ6abp/sPgbAMjTDnDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ee8c9582b191d102cdf0c376ddb3f3fbcd1a71081da8a027f9ba09817d694d6a","last_reissued_at":"2026-05-18T00:41:18.131975Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:41:18.131975Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Node Embedding via Word Embedding for Network Community Discovery","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.soc-ph","stat.ML"],"primary_cat":"cs.SI","authors_text":"Christy Lin, Prakash Ishwar, Weicong Ding","submitted_at":"2016-11-09T17:59:13Z","abstract_excerpt":"Neural node embeddings have recently emerged as a powerful representation for supervised learning tasks involving graph-structured data. We leverage this recent advance to develop a novel algorithm for unsupervised community discovery in graphs. Through extensive experimental studies on simulated and real-world data, we demonstrate that the proposed approach consistently improves over the current state-of-the-art. Specifically, our approach empirically attains the information-theoretic limits for community recovery under the benchmark Stochastic Block Models for graph generation and exhibits b"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.03028","kind":"arxiv","version":3},"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":"1611.03028","created_at":"2026-05-18T00:41:18.132103+00:00"},{"alias_kind":"arxiv_version","alias_value":"1611.03028v3","created_at":"2026-05-18T00:41:18.132103+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.03028","created_at":"2026-05-18T00:41:18.132103+00:00"},{"alias_kind":"pith_short_12","alias_value":"52GJLAVRSHIQ","created_at":"2026-05-18T12:29:58.707656+00:00"},{"alias_kind":"pith_short_16","alias_value":"52GJLAVRSHIQFTPQ","created_at":"2026-05-18T12:29:58.707656+00:00"},{"alias_kind":"pith_short_8","alias_value":"52GJLAVR","created_at":"2026-05-18T12:29:58.707656+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/52GJLAVRSHIQFTPQYN3N3M7T7P","json":"https://pith.science/pith/52GJLAVRSHIQFTPQYN3N3M7T7P.json","graph_json":"https://pith.science/api/pith-number/52GJLAVRSHIQFTPQYN3N3M7T7P/graph.json","events_json":"https://pith.science/api/pith-number/52GJLAVRSHIQFTPQYN3N3M7T7P/events.json","paper":"https://pith.science/paper/52GJLAVR"},"agent_actions":{"view_html":"https://pith.science/pith/52GJLAVRSHIQFTPQYN3N3M7T7P","download_json":"https://pith.science/pith/52GJLAVRSHIQFTPQYN3N3M7T7P.json","view_paper":"https://pith.science/paper/52GJLAVR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1611.03028&json=true","fetch_graph":"https://pith.science/api/pith-number/52GJLAVRSHIQFTPQYN3N3M7T7P/graph.json","fetch_events":"https://pith.science/api/pith-number/52GJLAVRSHIQFTPQYN3N3M7T7P/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/52GJLAVRSHIQFTPQYN3N3M7T7P/action/timestamp_anchor","attest_storage":"https://pith.science/pith/52GJLAVRSHIQFTPQYN3N3M7T7P/action/storage_attestation","attest_author":"https://pith.science/pith/52GJLAVRSHIQFTPQYN3N3M7T7P/action/author_attestation","sign_citation":"https://pith.science/pith/52GJLAVRSHIQFTPQYN3N3M7T7P/action/citation_signature","submit_replication":"https://pith.science/pith/52GJLAVRSHIQFTPQYN3N3M7T7P/action/replication_record"}},"created_at":"2026-05-18T00:41:18.132103+00:00","updated_at":"2026-05-18T00:41:18.132103+00:00"}