{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:AUO7SZARCI3XX5OJJUBBSCFBZI","short_pith_number":"pith:AUO7SZAR","schema_version":"1.0","canonical_sha256":"051df9641112377bf5c94d021908a1ca2bfb1ec1944964ce564239ae11f609ca","source":{"kind":"arxiv","id":"2010.12882","version":1},"attestation_state":"computed","paper":{"title":"FedE: Embedding Knowledge Graphs in Federated Setting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Huajun Chen, Mingyang Chen, Wen Zhang, Yantao Jia, Zonggang Yuan","submitted_at":"2020-10-24T11:52:05Z","abstract_excerpt":"Knowledge graphs (KGs) consisting of triples are always incomplete, so it's important to do Knowledge Graph Completion (KGC) by predicting missing triples. Multi-Source KG is a common situation in real KG applications which can be viewed as a set of related individual KGs where different KGs contains relations of different aspects of entities. It's intuitive that, for each individual KG, its completion could be greatly contributed by the triples defined and labeled in other ones. However, because of the data privacy and sensitivity, a set of relevant knowledge graphs cannot complement each oth"},"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":"2010.12882","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-24T11:52:05Z","cross_cats_sorted":[],"title_canon_sha256":"a825ecf35ddf3ce26a294c59c465aac8cb28b51a092cd1020d08d52007738bdc","abstract_canon_sha256":"f83a5e3b5018152e200914e04c85bc7eae91968deba62589835790b1a05719cd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:45:49.330267Z","signature_b64":"jAAJDDONRVK0GyIm20Vq2y6ZBuFU+dEc1YDyl7mspJRzR5z7StWKrMfuhXbIhcyGs47kzh5xQK8110yeXTO/Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"051df9641112377bf5c94d021908a1ca2bfb1ec1944964ce564239ae11f609ca","last_reissued_at":"2026-07-05T01:45:49.329801Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:45:49.329801Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FedE: Embedding Knowledge Graphs in Federated Setting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Huajun Chen, Mingyang Chen, Wen Zhang, Yantao Jia, Zonggang Yuan","submitted_at":"2020-10-24T11:52:05Z","abstract_excerpt":"Knowledge graphs (KGs) consisting of triples are always incomplete, so it's important to do Knowledge Graph Completion (KGC) by predicting missing triples. Multi-Source KG is a common situation in real KG applications which can be viewed as a set of related individual KGs where different KGs contains relations of different aspects of entities. It's intuitive that, for each individual KG, its completion could be greatly contributed by the triples defined and labeled in other ones. However, because of the data privacy and sensitivity, a set of relevant knowledge graphs cannot complement each oth"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.12882","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2010.12882/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2010.12882","created_at":"2026-07-05T01:45:49.329855+00:00"},{"alias_kind":"arxiv_version","alias_value":"2010.12882v1","created_at":"2026-07-05T01:45:49.329855+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.12882","created_at":"2026-07-05T01:45:49.329855+00:00"},{"alias_kind":"pith_short_12","alias_value":"AUO7SZARCI3X","created_at":"2026-07-05T01:45:49.329855+00:00"},{"alias_kind":"pith_short_16","alias_value":"AUO7SZARCI3XX5OJ","created_at":"2026-07-05T01:45:49.329855+00:00"},{"alias_kind":"pith_short_8","alias_value":"AUO7SZAR","created_at":"2026-07-05T01:45:49.329855+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/AUO7SZARCI3XX5OJJUBBSCFBZI","json":"https://pith.science/pith/AUO7SZARCI3XX5OJJUBBSCFBZI.json","graph_json":"https://pith.science/api/pith-number/AUO7SZARCI3XX5OJJUBBSCFBZI/graph.json","events_json":"https://pith.science/api/pith-number/AUO7SZARCI3XX5OJJUBBSCFBZI/events.json","paper":"https://pith.science/paper/AUO7SZAR"},"agent_actions":{"view_html":"https://pith.science/pith/AUO7SZARCI3XX5OJJUBBSCFBZI","download_json":"https://pith.science/pith/AUO7SZARCI3XX5OJJUBBSCFBZI.json","view_paper":"https://pith.science/paper/AUO7SZAR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2010.12882&json=true","fetch_graph":"https://pith.science/api/pith-number/AUO7SZARCI3XX5OJJUBBSCFBZI/graph.json","fetch_events":"https://pith.science/api/pith-number/AUO7SZARCI3XX5OJJUBBSCFBZI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AUO7SZARCI3XX5OJJUBBSCFBZI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AUO7SZARCI3XX5OJJUBBSCFBZI/action/storage_attestation","attest_author":"https://pith.science/pith/AUO7SZARCI3XX5OJJUBBSCFBZI/action/author_attestation","sign_citation":"https://pith.science/pith/AUO7SZARCI3XX5OJJUBBSCFBZI/action/citation_signature","submit_replication":"https://pith.science/pith/AUO7SZARCI3XX5OJJUBBSCFBZI/action/replication_record"}},"created_at":"2026-07-05T01:45:49.329855+00:00","updated_at":"2026-07-05T01:45:49.329855+00:00"}