{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:6P36Y74OLBFARHWP3YBIJQ3VYX","short_pith_number":"pith:6P36Y74O","canonical_record":{"source":{"id":"1304.8016","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2013-04-23T22:14:18Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"5689a3e29dfd180d9225cbcc28a53eef72c182f4ee68a96dcf055e839b352c15","abstract_canon_sha256":"51f7255176a6b73aa5297de9d9f5bd95f04349fb81eb2f1885cd4e1d20705c02"},"schema_version":"1.0"},"canonical_sha256":"f3f7ec7f8e584a089ecfde0284c375c5c86e9ec34b3f9a9ccc30def29e6eed92","source":{"kind":"arxiv","id":"1304.8016","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1304.8016","created_at":"2026-05-18T03:26:51Z"},{"alias_kind":"arxiv_version","alias_value":"1304.8016v1","created_at":"2026-05-18T03:26:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1304.8016","created_at":"2026-05-18T03:26:51Z"},{"alias_kind":"pith_short_12","alias_value":"6P36Y74OLBFA","created_at":"2026-05-18T12:27:36Z"},{"alias_kind":"pith_short_16","alias_value":"6P36Y74OLBFARHWP","created_at":"2026-05-18T12:27:36Z"},{"alias_kind":"pith_short_8","alias_value":"6P36Y74O","created_at":"2026-05-18T12:27:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:6P36Y74OLBFARHWP3YBIJQ3VYX","target":"record","payload":{"canonical_record":{"source":{"id":"1304.8016","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2013-04-23T22:14:18Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"5689a3e29dfd180d9225cbcc28a53eef72c182f4ee68a96dcf055e839b352c15","abstract_canon_sha256":"51f7255176a6b73aa5297de9d9f5bd95f04349fb81eb2f1885cd4e1d20705c02"},"schema_version":"1.0"},"canonical_sha256":"f3f7ec7f8e584a089ecfde0284c375c5c86e9ec34b3f9a9ccc30def29e6eed92","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:26:51.140896Z","signature_b64":"fKDDH8jsdKlhMClYK2rqBbsZAXJTz5EtJDO9Sm4awDgHY/j2I2zlBj2DxkwBoYYS0CoexLEBU0ide1fISuAuDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f3f7ec7f8e584a089ecfde0284c375c5c86e9ec34b3f9a9ccc30def29e6eed92","last_reissued_at":"2026-05-18T03:26:51.140295Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:26:51.140295Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1304.8016","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":"2026-05-18T03:26:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4RABwjrC2aRxOGZVRUsFXHYeQVl/cZm3VAHdH7Cj+69lf7qWkbPHjPQCbWWMwbEBHIVi/f4y5K4U0HlIIMlwCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T19:05:41.622412Z"},"content_sha256":"c5122224e7207aead154aebe54066f9f5c67e6962bc60e91864f1a71d854d5e2","schema_version":"1.0","event_id":"sha256:c5122224e7207aead154aebe54066f9f5c67e6962bc60e91864f1a71d854d5e2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:6P36Y74OLBFARHWP3YBIJQ3VYX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On Semantic Word Cloud Representation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.DS","authors_text":"Lukas Barth, Sergey Pupyrev, Stephen Kobourov, Torsten Ueckerdt","submitted_at":"2013-04-23T22:14:18Z","abstract_excerpt":"We study the problem of computing semantic-preserving word clouds in which semantically related words are close to each other. While several heuristic approaches have been described in the literature, we formalize the underlying geometric algorithm problem: Word Rectangle Adjacency Contact (WRAC). In this model each word is associated with rectangle with fixed dimensions, and the goal is to represent semantically related words by ensuring that the two corresponding rectangles touch. We design and analyze efficient polynomial-time algorithms for some variants of the WRAC problem, show that seve"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1304.8016","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":"2026-05-18T03:26:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xw5RlxV8ItWNeRmBxQC+WCWXXdKZVgdHymYmbfSSo443OYOmtmxUg1/VNJHdA1ETnzlleKCsMw4lhmH4p8NtCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T19:05:41.622757Z"},"content_sha256":"ca3f56d42076a852a0aac2060d3c88ab3973374100dfbba97020e67ce1d45a62","schema_version":"1.0","event_id":"sha256:ca3f56d42076a852a0aac2060d3c88ab3973374100dfbba97020e67ce1d45a62"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6P36Y74OLBFARHWP3YBIJQ3VYX/bundle.json","state_url":"https://pith.science/pith/6P36Y74OLBFARHWP3YBIJQ3VYX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6P36Y74OLBFARHWP3YBIJQ3VYX/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":"2026-06-01T19:05:41Z","links":{"resolver":"https://pith.science/pith/6P36Y74OLBFARHWP3YBIJQ3VYX","bundle":"https://pith.science/pith/6P36Y74OLBFARHWP3YBIJQ3VYX/bundle.json","state":"https://pith.science/pith/6P36Y74OLBFARHWP3YBIJQ3VYX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6P36Y74OLBFARHWP3YBIJQ3VYX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:6P36Y74OLBFARHWP3YBIJQ3VYX","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":"51f7255176a6b73aa5297de9d9f5bd95f04349fb81eb2f1885cd4e1d20705c02","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2013-04-23T22:14:18Z","title_canon_sha256":"5689a3e29dfd180d9225cbcc28a53eef72c182f4ee68a96dcf055e839b352c15"},"schema_version":"1.0","source":{"id":"1304.8016","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1304.8016","created_at":"2026-05-18T03:26:51Z"},{"alias_kind":"arxiv_version","alias_value":"1304.8016v1","created_at":"2026-05-18T03:26:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1304.8016","created_at":"2026-05-18T03:26:51Z"},{"alias_kind":"pith_short_12","alias_value":"6P36Y74OLBFA","created_at":"2026-05-18T12:27:36Z"},{"alias_kind":"pith_short_16","alias_value":"6P36Y74OLBFARHWP","created_at":"2026-05-18T12:27:36Z"},{"alias_kind":"pith_short_8","alias_value":"6P36Y74O","created_at":"2026-05-18T12:27:36Z"}],"graph_snapshots":[{"event_id":"sha256:ca3f56d42076a852a0aac2060d3c88ab3973374100dfbba97020e67ce1d45a62","target":"graph","created_at":"2026-05-18T03:26:51Z","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":"We study the problem of computing semantic-preserving word clouds in which semantically related words are close to each other. While several heuristic approaches have been described in the literature, we formalize the underlying geometric algorithm problem: Word Rectangle Adjacency Contact (WRAC). In this model each word is associated with rectangle with fixed dimensions, and the goal is to represent semantically related words by ensuring that the two corresponding rectangles touch. We design and analyze efficient polynomial-time algorithms for some variants of the WRAC problem, show that seve","authors_text":"Lukas Barth, Sergey Pupyrev, Stephen Kobourov, Torsten Ueckerdt","cross_cats":["cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2013-04-23T22:14:18Z","title":"On Semantic Word Cloud Representation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1304.8016","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:c5122224e7207aead154aebe54066f9f5c67e6962bc60e91864f1a71d854d5e2","target":"record","created_at":"2026-05-18T03:26:51Z","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":"51f7255176a6b73aa5297de9d9f5bd95f04349fb81eb2f1885cd4e1d20705c02","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2013-04-23T22:14:18Z","title_canon_sha256":"5689a3e29dfd180d9225cbcc28a53eef72c182f4ee68a96dcf055e839b352c15"},"schema_version":"1.0","source":{"id":"1304.8016","kind":"arxiv","version":1}},"canonical_sha256":"f3f7ec7f8e584a089ecfde0284c375c5c86e9ec34b3f9a9ccc30def29e6eed92","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f3f7ec7f8e584a089ecfde0284c375c5c86e9ec34b3f9a9ccc30def29e6eed92","first_computed_at":"2026-05-18T03:26:51.140295Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:26:51.140295Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fKDDH8jsdKlhMClYK2rqBbsZAXJTz5EtJDO9Sm4awDgHY/j2I2zlBj2DxkwBoYYS0CoexLEBU0ide1fISuAuDg==","signature_status":"signed_v1","signed_at":"2026-05-18T03:26:51.140896Z","signed_message":"canonical_sha256_bytes"},"source_id":"1304.8016","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c5122224e7207aead154aebe54066f9f5c67e6962bc60e91864f1a71d854d5e2","sha256:ca3f56d42076a852a0aac2060d3c88ab3973374100dfbba97020e67ce1d45a62"],"state_sha256":"021d0ec0aa9faface601418d305d7586152cdbd0492cc40067c1257e614b3cd7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QVkTk4aDk6s0M/2o7lBcmffW/uvEqLculSJReWlMVwA8vuxelEGmCegP12kj228qTWhQ62AV6lHeC6rrD4YWAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T19:05:41.624653Z","bundle_sha256":"65bd9e70f6e2f2cda748df33311b5ca9f3488443b890a49caee966eceb5b960f"}}