{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:DLP3E76CUMNR6HW3VSZXKJ65RV","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":"9e214a03f4d46edbc32cae8374d07f841c27b5a40376f370e401f7b7c734bed6","cross_cats_sorted":["cs.LG","cs.NA","math.NA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2022-02-28T19:00:49Z","title_canon_sha256":"c959a0e35690df71990a13073ef02e99ee9a02c9be3b9041c6e927b8b5819afd"},"schema_version":"1.0","source":{"id":"2203.03551","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.03551","created_at":"2026-07-05T04:02:35Z"},{"alias_kind":"arxiv_version","alias_value":"2203.03551v1","created_at":"2026-07-05T04:02:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.03551","created_at":"2026-07-05T04:02:35Z"},{"alias_kind":"pith_short_12","alias_value":"DLP3E76CUMNR","created_at":"2026-07-05T04:02:35Z"},{"alias_kind":"pith_short_16","alias_value":"DLP3E76CUMNR6HW3","created_at":"2026-07-05T04:02:35Z"},{"alias_kind":"pith_short_8","alias_value":"DLP3E76C","created_at":"2026-07-05T04:02:35Z"}],"graph_snapshots":[{"event_id":"sha256:6c4f1c83f3176fb50c17e98ee50f138dbd82b2f8acf0ceea8f3cbc4b4356c905","target":"graph","created_at":"2026-07-05T04:02:35Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2203.03551/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose new semi-supervised nonnegative matrix factorization (SSNMF) models for document classification and provide motivation for these models as maximum likelihood estimators. The proposed SSNMF models simultaneously provide both a topic model and a model for classification, thereby offering highly interpretable classification results. We derive training methods using multiplicative updates for each new model, and demonstrate the application of these models to single-label and multi-label document classification, although the models are flexible to other supervised learning tasks such as ","authors_text":"Alona Kryshchenko, Chuntian Wang, Deanna Needell, Elena Sizikova, Jamie Haddock, Kathryn Leonard, Lara Kassab, Miju Ahn, Rachel Grotheer, RWMA Madushani, Sixian Li, Thomas Merkh","cross_cats":["cs.LG","cs.NA","math.NA"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2022-02-28T19:00:49Z","title":"Semi-supervised Nonnegative Matrix Factorization for Document Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.03551","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":"sha256:52d36cfcc9c74b4bc63613c410f11fca429eb0c876d3ca33b15e970157187f52","target":"record","created_at":"2026-07-05T04:02:35Z","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":"9e214a03f4d46edbc32cae8374d07f841c27b5a40376f370e401f7b7c734bed6","cross_cats_sorted":["cs.LG","cs.NA","math.NA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2022-02-28T19:00:49Z","title_canon_sha256":"c959a0e35690df71990a13073ef02e99ee9a02c9be3b9041c6e927b8b5819afd"},"schema_version":"1.0","source":{"id":"2203.03551","kind":"arxiv","version":1}},"canonical_sha256":"1adfb27fc2a31b1f1edbacb37527dd8d5ea953dd33a9d3c060439c6b9b7675c5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1adfb27fc2a31b1f1edbacb37527dd8d5ea953dd33a9d3c060439c6b9b7675c5","first_computed_at":"2026-07-05T04:02:35.527547Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:02:35.527547Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cgrT2eDYS46ctXZKf0mi9VcpK6Gd14ytcED238u5pu+Mk1RoD1nx6pySh6ka0oQlRKpsF3WcpKrd2cK/WD6YBw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:02:35.527949Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.03551","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:52d36cfcc9c74b4bc63613c410f11fca429eb0c876d3ca33b15e970157187f52","sha256:6c4f1c83f3176fb50c17e98ee50f138dbd82b2f8acf0ceea8f3cbc4b4356c905"],"state_sha256":"53005b1f103c04f4f6b8b47f4ef8f59e9c6ff3da41873ff435208ae77e025610"}