{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:G4OXV4XBTUCG4KMRVDNSEAWZUN","short_pith_number":"pith:G4OXV4XB","canonical_record":{"source":{"id":"1811.12199","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2018-11-28T01:47:49Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"f2422ffef76609d6668c5d0382fe9e20a1d8d14b9796400f49e0dbc5b0ee58e4","abstract_canon_sha256":"dc516548abf68351b10b1a8d21b28884208803be1e313d858ea4eddcc366ba63"},"schema_version":"1.0"},"canonical_sha256":"371d7af2e19d046e2991a8db2202d9a3714d7d9c46b3a6fe71bb0b1f0e5aebf2","source":{"kind":"arxiv","id":"1811.12199","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.12199","created_at":"2026-05-17T23:59:34Z"},{"alias_kind":"arxiv_version","alias_value":"1811.12199v1","created_at":"2026-05-17T23:59:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.12199","created_at":"2026-05-17T23:59:34Z"},{"alias_kind":"pith_short_12","alias_value":"G4OXV4XBTUCG","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"G4OXV4XBTUCG4KMR","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"G4OXV4XB","created_at":"2026-05-18T12:32:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:G4OXV4XBTUCG4KMRVDNSEAWZUN","target":"record","payload":{"canonical_record":{"source":{"id":"1811.12199","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2018-11-28T01:47:49Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"f2422ffef76609d6668c5d0382fe9e20a1d8d14b9796400f49e0dbc5b0ee58e4","abstract_canon_sha256":"dc516548abf68351b10b1a8d21b28884208803be1e313d858ea4eddcc366ba63"},"schema_version":"1.0"},"canonical_sha256":"371d7af2e19d046e2991a8db2202d9a3714d7d9c46b3a6fe71bb0b1f0e5aebf2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:59:34.106503Z","signature_b64":"7MavhKu9gDXuKWPfid6NRPaCWL3epnpQobQ0l+yONGAD0cOA2WzBpoch3bGPG95FpawjmjTg0/O1RxdSEAqSCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"371d7af2e19d046e2991a8db2202d9a3714d7d9c46b3a6fe71bb0b1f0e5aebf2","last_reissued_at":"2026-05-17T23:59:34.105871Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:59:34.105871Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.12199","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:59:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+w5XGmKotncdh/xUeTXJpCeRZFP7f2ar0kyEZxojHpi0H06nejFyuaItWl3TgnlkFdv69Osa9zv/sIt3t6MmAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T07:51:35.241782Z"},"content_sha256":"955f9446da024a2a353a1b2e9096a96f12f74ceca32217671f0b4a9a9ba43725","schema_version":"1.0","event_id":"sha256:955f9446da024a2a353a1b2e9096a96f12f74ceca32217671f0b4a9a9ba43725"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:G4OXV4XBTUCG4KMRVDNSEAWZUN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Visual Interaction Framework for Dimensionality Reduction Based Data Exploration","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.HC","authors_text":"\\c{C}a\\u{g}atay Demiralp, Marco Cavallo","submitted_at":"2018-11-28T01:47:49Z","abstract_excerpt":"Dimensionality reduction is a common method for analyzing and visualizing high-dimensional data. However, reasoning dynamically about the results of a dimensionality reduction is difficult. Dimensionality-reduction algorithms use complex optimizations to reduce the number of dimensions of a dataset, but these new dimensions often lack a clear relation to the initial data dimensions, thus making them difficult to interpret. Here we propose a visual interaction framework to improve dimensionality-reduction based exploratory data analysis. We introduce two interaction techniques, forward projecti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.12199","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:59:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0kaCoPDHTSb8bflYephKIBTCQ1DzeRjUdSoLDqhyeaM/nmrHd3qc8qTsl+jD3tWGRoT3MFmIEwVB8/uCBJXQBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T07:51:35.242131Z"},"content_sha256":"8cb3eac6bd9dd217b875a556a0a811fbb5a6113e674c11de2641941073f28801","schema_version":"1.0","event_id":"sha256:8cb3eac6bd9dd217b875a556a0a811fbb5a6113e674c11de2641941073f28801"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G4OXV4XBTUCG4KMRVDNSEAWZUN/bundle.json","state_url":"https://pith.science/pith/G4OXV4XBTUCG4KMRVDNSEAWZUN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G4OXV4XBTUCG4KMRVDNSEAWZUN/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-24T07:51:35Z","links":{"resolver":"https://pith.science/pith/G4OXV4XBTUCG4KMRVDNSEAWZUN","bundle":"https://pith.science/pith/G4OXV4XBTUCG4KMRVDNSEAWZUN/bundle.json","state":"https://pith.science/pith/G4OXV4XBTUCG4KMRVDNSEAWZUN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G4OXV4XBTUCG4KMRVDNSEAWZUN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:G4OXV4XBTUCG4KMRVDNSEAWZUN","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":"dc516548abf68351b10b1a8d21b28884208803be1e313d858ea4eddcc366ba63","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2018-11-28T01:47:49Z","title_canon_sha256":"f2422ffef76609d6668c5d0382fe9e20a1d8d14b9796400f49e0dbc5b0ee58e4"},"schema_version":"1.0","source":{"id":"1811.12199","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.12199","created_at":"2026-05-17T23:59:34Z"},{"alias_kind":"arxiv_version","alias_value":"1811.12199v1","created_at":"2026-05-17T23:59:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.12199","created_at":"2026-05-17T23:59:34Z"},{"alias_kind":"pith_short_12","alias_value":"G4OXV4XBTUCG","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"G4OXV4XBTUCG4KMR","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"G4OXV4XB","created_at":"2026-05-18T12:32:25Z"}],"graph_snapshots":[{"event_id":"sha256:8cb3eac6bd9dd217b875a556a0a811fbb5a6113e674c11de2641941073f28801","target":"graph","created_at":"2026-05-17T23:59:34Z","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"},"paper":{"abstract_excerpt":"Dimensionality reduction is a common method for analyzing and visualizing high-dimensional data. However, reasoning dynamically about the results of a dimensionality reduction is difficult. Dimensionality-reduction algorithms use complex optimizations to reduce the number of dimensions of a dataset, but these new dimensions often lack a clear relation to the initial data dimensions, thus making them difficult to interpret. Here we propose a visual interaction framework to improve dimensionality-reduction based exploratory data analysis. We introduce two interaction techniques, forward projecti","authors_text":"\\c{C}a\\u{g}atay Demiralp, Marco Cavallo","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2018-11-28T01:47:49Z","title":"A Visual Interaction Framework for Dimensionality Reduction Based Data Exploration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.12199","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":"sha256:955f9446da024a2a353a1b2e9096a96f12f74ceca32217671f0b4a9a9ba43725","target":"record","created_at":"2026-05-17T23:59:34Z","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":"dc516548abf68351b10b1a8d21b28884208803be1e313d858ea4eddcc366ba63","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2018-11-28T01:47:49Z","title_canon_sha256":"f2422ffef76609d6668c5d0382fe9e20a1d8d14b9796400f49e0dbc5b0ee58e4"},"schema_version":"1.0","source":{"id":"1811.12199","kind":"arxiv","version":1}},"canonical_sha256":"371d7af2e19d046e2991a8db2202d9a3714d7d9c46b3a6fe71bb0b1f0e5aebf2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"371d7af2e19d046e2991a8db2202d9a3714d7d9c46b3a6fe71bb0b1f0e5aebf2","first_computed_at":"2026-05-17T23:59:34.105871Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:59:34.105871Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7MavhKu9gDXuKWPfid6NRPaCWL3epnpQobQ0l+yONGAD0cOA2WzBpoch3bGPG95FpawjmjTg0/O1RxdSEAqSCQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:59:34.106503Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.12199","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:955f9446da024a2a353a1b2e9096a96f12f74ceca32217671f0b4a9a9ba43725","sha256:8cb3eac6bd9dd217b875a556a0a811fbb5a6113e674c11de2641941073f28801"],"state_sha256":"003cdbe31683ef8314a1006c31004b66f0284d30aae78723e44ca379b24f081a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cR9wf+q3dZeo8oqJbI36C1BtZdCTQXN/YwX2fCGV6Qt5oGU8lhnUQ3VWNPNPg6di42MKxIevbXM+7kEZp4yBAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-24T07:51:35.244222Z","bundle_sha256":"52731e90e22718be84de8098d041f09e31442a951a30aa757f5153713ec8eb19"}}