{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:45FR3GPUDFG6JY2JW74DFA5CX2","short_pith_number":"pith:45FR3GPU","schema_version":"1.0","canonical_sha256":"e74b1d99f4194de4e349b7f83283a2beb31af17280360880df2484a22fed0f73","source":{"kind":"arxiv","id":"1812.09481","version":1},"attestation_state":"computed","paper":{"title":"Bi-clustering for time-varying relational count data analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Hiroshi Yadohisa, Mariko Takagishi, Satoshi Goto","submitted_at":"2018-12-22T09:07:05Z","abstract_excerpt":"Relational count data are often obtained from sources such as simultaneous purchase in online shops and social networking service information. Bi-clustering such relational count data reveals the latent structure of the relationship between objects such as household items or people. When relational count data observed at multiple time points are available, it is worthwhile incorporating the time structure into the bi-clustering result to understand how objects move between the cluster over time. In this paper, we propose two bi-clustering methods for analyzing time-varying relational count dat"},"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":"1812.09481","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2018-12-22T09:07:05Z","cross_cats_sorted":[],"title_canon_sha256":"2182ab7d9c7b54c335bea4573be2ec5b13ed9f70fd5c86cd4e9534bc38ffcdf6","abstract_canon_sha256":"5a7bfd61e01714087131f4a1a11b26710d85c54c1796399968a044c25135c3ae"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:57:27.816530Z","signature_b64":"Mrdjb8fOzxcPm9cdqAHk5+0GpRtF0GLzmGL33IpgtfhafRcc/8dkQJfmeruC1PKW6GZaxbcO02Q/jih5SI7DAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e74b1d99f4194de4e349b7f83283a2beb31af17280360880df2484a22fed0f73","last_reissued_at":"2026-05-17T23:57:27.815832Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:57:27.815832Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Bi-clustering for time-varying relational count data analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Hiroshi Yadohisa, Mariko Takagishi, Satoshi Goto","submitted_at":"2018-12-22T09:07:05Z","abstract_excerpt":"Relational count data are often obtained from sources such as simultaneous purchase in online shops and social networking service information. Bi-clustering such relational count data reveals the latent structure of the relationship between objects such as household items or people. When relational count data observed at multiple time points are available, it is worthwhile incorporating the time structure into the bi-clustering result to understand how objects move between the cluster over time. In this paper, we propose two bi-clustering methods for analyzing time-varying relational count dat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.09481","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":"1812.09481","created_at":"2026-05-17T23:57:27.815949+00:00"},{"alias_kind":"arxiv_version","alias_value":"1812.09481v1","created_at":"2026-05-17T23:57:27.815949+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.09481","created_at":"2026-05-17T23:57:27.815949+00:00"},{"alias_kind":"pith_short_12","alias_value":"45FR3GPUDFG6","created_at":"2026-05-18T12:32:05.422762+00:00"},{"alias_kind":"pith_short_16","alias_value":"45FR3GPUDFG6JY2J","created_at":"2026-05-18T12:32:05.422762+00:00"},{"alias_kind":"pith_short_8","alias_value":"45FR3GPU","created_at":"2026-05-18T12:32:05.422762+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/45FR3GPUDFG6JY2JW74DFA5CX2","json":"https://pith.science/pith/45FR3GPUDFG6JY2JW74DFA5CX2.json","graph_json":"https://pith.science/api/pith-number/45FR3GPUDFG6JY2JW74DFA5CX2/graph.json","events_json":"https://pith.science/api/pith-number/45FR3GPUDFG6JY2JW74DFA5CX2/events.json","paper":"https://pith.science/paper/45FR3GPU"},"agent_actions":{"view_html":"https://pith.science/pith/45FR3GPUDFG6JY2JW74DFA5CX2","download_json":"https://pith.science/pith/45FR3GPUDFG6JY2JW74DFA5CX2.json","view_paper":"https://pith.science/paper/45FR3GPU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1812.09481&json=true","fetch_graph":"https://pith.science/api/pith-number/45FR3GPUDFG6JY2JW74DFA5CX2/graph.json","fetch_events":"https://pith.science/api/pith-number/45FR3GPUDFG6JY2JW74DFA5CX2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/45FR3GPUDFG6JY2JW74DFA5CX2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/45FR3GPUDFG6JY2JW74DFA5CX2/action/storage_attestation","attest_author":"https://pith.science/pith/45FR3GPUDFG6JY2JW74DFA5CX2/action/author_attestation","sign_citation":"https://pith.science/pith/45FR3GPUDFG6JY2JW74DFA5CX2/action/citation_signature","submit_replication":"https://pith.science/pith/45FR3GPUDFG6JY2JW74DFA5CX2/action/replication_record"}},"created_at":"2026-05-17T23:57:27.815949+00:00","updated_at":"2026-05-17T23:57:27.815949+00:00"}