{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:UHMBC4WSSDK2R7UP4AKLDEVU6J","short_pith_number":"pith:UHMBC4WS","schema_version":"1.0","canonical_sha256":"a1d81172d290d5a8fe8fe014b192b4f243dcaf0dd33d40f1474d673aedccf3f1","source":{"kind":"arxiv","id":"1803.02533","version":1},"attestation_state":"computed","paper":{"title":"MetaGraph2Vec: Complex Semantic Path Augmented Heterogeneous Network Embedding","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Chengqi Zhang, Daokun Zhang, Jie Yin, Xingquan Zhu","submitted_at":"2018-03-07T05:57:44Z","abstract_excerpt":"Network embedding in heterogeneous information networks (HINs) is a challenging task, due to complications of different node types and rich relationships between nodes. As a result, conventional network embedding techniques cannot work on such HINs. Recently, metapath-based approaches have been proposed to characterize relationships in HINs, but they are ineffective in capturing rich contexts and semantics between nodes for embedding learning, mainly because (1) metapath is a rather strict single path node-node relationship descriptor, which is unable to accommodate variance in relationships, "},"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":"1803.02533","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.SI","submitted_at":"2018-03-07T05:57:44Z","cross_cats_sorted":[],"title_canon_sha256":"893b881ac9df3a696da234f8284ac63e8b4cc0445ce9ee102b9abac1b72ead82","abstract_canon_sha256":"a0efbdae4892d6bb54ca26f0fee2b6623ae93486b997702f9fcf35924b5f19d1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:21:50.015269Z","signature_b64":"3kA7GlXthWfROBCX7A4GGby35FBcANc46v68C52/AHPhqitMbBMrXBKzagHbugRRrZ3Sm02Dqb9xY9r9GiKgDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a1d81172d290d5a8fe8fe014b192b4f243dcaf0dd33d40f1474d673aedccf3f1","last_reissued_at":"2026-05-18T00:21:50.014640Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:21:50.014640Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MetaGraph2Vec: Complex Semantic Path Augmented Heterogeneous Network Embedding","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Chengqi Zhang, Daokun Zhang, Jie Yin, Xingquan Zhu","submitted_at":"2018-03-07T05:57:44Z","abstract_excerpt":"Network embedding in heterogeneous information networks (HINs) is a challenging task, due to complications of different node types and rich relationships between nodes. As a result, conventional network embedding techniques cannot work on such HINs. Recently, metapath-based approaches have been proposed to characterize relationships in HINs, but they are ineffective in capturing rich contexts and semantics between nodes for embedding learning, mainly because (1) metapath is a rather strict single path node-node relationship descriptor, which is unable to accommodate variance in relationships, "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.02533","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":"1803.02533","created_at":"2026-05-18T00:21:50.014733+00:00"},{"alias_kind":"arxiv_version","alias_value":"1803.02533v1","created_at":"2026-05-18T00:21:50.014733+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.02533","created_at":"2026-05-18T00:21:50.014733+00:00"},{"alias_kind":"pith_short_12","alias_value":"UHMBC4WSSDK2","created_at":"2026-05-18T12:32:56.356000+00:00"},{"alias_kind":"pith_short_16","alias_value":"UHMBC4WSSDK2R7UP","created_at":"2026-05-18T12:32:56.356000+00:00"},{"alias_kind":"pith_short_8","alias_value":"UHMBC4WS","created_at":"2026-05-18T12:32:56.356000+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/UHMBC4WSSDK2R7UP4AKLDEVU6J","json":"https://pith.science/pith/UHMBC4WSSDK2R7UP4AKLDEVU6J.json","graph_json":"https://pith.science/api/pith-number/UHMBC4WSSDK2R7UP4AKLDEVU6J/graph.json","events_json":"https://pith.science/api/pith-number/UHMBC4WSSDK2R7UP4AKLDEVU6J/events.json","paper":"https://pith.science/paper/UHMBC4WS"},"agent_actions":{"view_html":"https://pith.science/pith/UHMBC4WSSDK2R7UP4AKLDEVU6J","download_json":"https://pith.science/pith/UHMBC4WSSDK2R7UP4AKLDEVU6J.json","view_paper":"https://pith.science/paper/UHMBC4WS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1803.02533&json=true","fetch_graph":"https://pith.science/api/pith-number/UHMBC4WSSDK2R7UP4AKLDEVU6J/graph.json","fetch_events":"https://pith.science/api/pith-number/UHMBC4WSSDK2R7UP4AKLDEVU6J/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UHMBC4WSSDK2R7UP4AKLDEVU6J/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UHMBC4WSSDK2R7UP4AKLDEVU6J/action/storage_attestation","attest_author":"https://pith.science/pith/UHMBC4WSSDK2R7UP4AKLDEVU6J/action/author_attestation","sign_citation":"https://pith.science/pith/UHMBC4WSSDK2R7UP4AKLDEVU6J/action/citation_signature","submit_replication":"https://pith.science/pith/UHMBC4WSSDK2R7UP4AKLDEVU6J/action/replication_record"}},"created_at":"2026-05-18T00:21:50.014733+00:00","updated_at":"2026-05-18T00:21:50.014733+00:00"}