{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:EYJJJIEL4BTGGGFPRNG7MHC5DB","short_pith_number":"pith:EYJJJIEL","schema_version":"1.0","canonical_sha256":"261294a08be0666318af8b4df61c5d184fcbb70722d0f7cb81964240c4477fea","source":{"kind":"arxiv","id":"1912.04896","version":3},"attestation_state":"computed","paper":{"title":"Self Organizing Nebulous Growths for Robust and Incremental Data Visualization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.HC","cs.LG"],"primary_cat":"cs.CV","authors_text":"Damith Senanayake, Saman Halgamuge, Shalin H. Naik, Wei Wang","submitted_at":"2019-12-09T22:11:51Z","abstract_excerpt":"Non-parametric dimensionality reduction techniques, such as t-SNE and UMAP, are proficient in providing visualizations for datasets of fixed sizes. However, they cannot incrementally map and insert new data points into an already provided data visualization. We present Self-Organizing Nebulous Growths (SONG), a parametric nonlinear dimensionality reduction technique that supports incremental data visualization, i.e., incremental addition of new data while preserving the structure of the existing visualization. In addition, SONG is capable of handling new data increments, no matter whether they"},"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":"1912.04896","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2019-12-09T22:11:51Z","cross_cats_sorted":["cs.HC","cs.LG"],"title_canon_sha256":"078bcc97fbfeea2729e6b6f65c1d1aaf4cd79644f557dff712550c7cdf9e8ed5","abstract_canon_sha256":"3961ee969334e92d66f39caa3a2ac531cfe66a3da8e274452c81eb5ed04783a3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:39:41.762504Z","signature_b64":"ASxkj9tr7TW3NtsGTx9NWmnkqzkY80py+Xmapfg5j19ANPPnzrQlFtgkr5kDGBdClbv5n2GeBgHMCNMpwZHyCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"261294a08be0666318af8b4df61c5d184fcbb70722d0f7cb81964240c4477fea","last_reissued_at":"2026-07-05T01:39:41.762149Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:39:41.762149Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Self Organizing Nebulous Growths for Robust and Incremental Data Visualization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.HC","cs.LG"],"primary_cat":"cs.CV","authors_text":"Damith Senanayake, Saman Halgamuge, Shalin H. Naik, Wei Wang","submitted_at":"2019-12-09T22:11:51Z","abstract_excerpt":"Non-parametric dimensionality reduction techniques, such as t-SNE and UMAP, are proficient in providing visualizations for datasets of fixed sizes. However, they cannot incrementally map and insert new data points into an already provided data visualization. We present Self-Organizing Nebulous Growths (SONG), a parametric nonlinear dimensionality reduction technique that supports incremental data visualization, i.e., incremental addition of new data while preserving the structure of the existing visualization. In addition, SONG is capable of handling new data increments, no matter whether they"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.04896","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1912.04896/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":"1912.04896","created_at":"2026-07-05T01:39:41.762204+00:00"},{"alias_kind":"arxiv_version","alias_value":"1912.04896v3","created_at":"2026-07-05T01:39:41.762204+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.04896","created_at":"2026-07-05T01:39:41.762204+00:00"},{"alias_kind":"pith_short_12","alias_value":"EYJJJIEL4BTG","created_at":"2026-07-05T01:39:41.762204+00:00"},{"alias_kind":"pith_short_16","alias_value":"EYJJJIEL4BTGGGFP","created_at":"2026-07-05T01:39:41.762204+00:00"},{"alias_kind":"pith_short_8","alias_value":"EYJJJIEL","created_at":"2026-07-05T01:39:41.762204+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/EYJJJIEL4BTGGGFPRNG7MHC5DB","json":"https://pith.science/pith/EYJJJIEL4BTGGGFPRNG7MHC5DB.json","graph_json":"https://pith.science/api/pith-number/EYJJJIEL4BTGGGFPRNG7MHC5DB/graph.json","events_json":"https://pith.science/api/pith-number/EYJJJIEL4BTGGGFPRNG7MHC5DB/events.json","paper":"https://pith.science/paper/EYJJJIEL"},"agent_actions":{"view_html":"https://pith.science/pith/EYJJJIEL4BTGGGFPRNG7MHC5DB","download_json":"https://pith.science/pith/EYJJJIEL4BTGGGFPRNG7MHC5DB.json","view_paper":"https://pith.science/paper/EYJJJIEL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1912.04896&json=true","fetch_graph":"https://pith.science/api/pith-number/EYJJJIEL4BTGGGFPRNG7MHC5DB/graph.json","fetch_events":"https://pith.science/api/pith-number/EYJJJIEL4BTGGGFPRNG7MHC5DB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/EYJJJIEL4BTGGGFPRNG7MHC5DB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/EYJJJIEL4BTGGGFPRNG7MHC5DB/action/storage_attestation","attest_author":"https://pith.science/pith/EYJJJIEL4BTGGGFPRNG7MHC5DB/action/author_attestation","sign_citation":"https://pith.science/pith/EYJJJIEL4BTGGGFPRNG7MHC5DB/action/citation_signature","submit_replication":"https://pith.science/pith/EYJJJIEL4BTGGGFPRNG7MHC5DB/action/replication_record"}},"created_at":"2026-07-05T01:39:41.762204+00:00","updated_at":"2026-07-05T01:39:41.762204+00:00"}