{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:6FUR5545RGJMLX2FPAZBLVNR5H","short_pith_number":"pith:6FUR5545","canonical_record":{"source":{"id":"2011.01773","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2020-11-03T15:13:05Z","cross_cats_sorted":[],"title_canon_sha256":"6d4e0de7d33ffe1ead7eb87fad49fe59bcb2aec7c287b20cae965309fdac9f7f","abstract_canon_sha256":"bace1d779906a30d6a8b77cb9fa6b2735584feec4018eaf95be1ad4af43fc2ff"},"schema_version":"1.0"},"canonical_sha256":"f1691ef79d8992c5df45783215d5b1e9ef341018828cdb19a025b9c2ab9765c4","source":{"kind":"arxiv","id":"2011.01773","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.01773","created_at":"2026-07-05T01:48:35Z"},{"alias_kind":"arxiv_version","alias_value":"2011.01773v1","created_at":"2026-07-05T01:48:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.01773","created_at":"2026-07-05T01:48:35Z"},{"alias_kind":"pith_short_12","alias_value":"6FUR5545RGJM","created_at":"2026-07-05T01:48:35Z"},{"alias_kind":"pith_short_16","alias_value":"6FUR5545RGJMLX2F","created_at":"2026-07-05T01:48:35Z"},{"alias_kind":"pith_short_8","alias_value":"6FUR5545","created_at":"2026-07-05T01:48:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:6FUR5545RGJMLX2FPAZBLVNR5H","target":"record","payload":{"canonical_record":{"source":{"id":"2011.01773","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2020-11-03T15:13:05Z","cross_cats_sorted":[],"title_canon_sha256":"6d4e0de7d33ffe1ead7eb87fad49fe59bcb2aec7c287b20cae965309fdac9f7f","abstract_canon_sha256":"bace1d779906a30d6a8b77cb9fa6b2735584feec4018eaf95be1ad4af43fc2ff"},"schema_version":"1.0"},"canonical_sha256":"f1691ef79d8992c5df45783215d5b1e9ef341018828cdb19a025b9c2ab9765c4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:48:35.845144Z","signature_b64":"PTkYj/vugwcDXc976EGzCs/ZJUztC79mE/rrJyh25+irIxNsLAzEBhTFjh8jdPf3+KW97fruarGEoZVdtm6XBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f1691ef79d8992c5df45783215d5b1e9ef341018828cdb19a025b9c2ab9765c4","last_reissued_at":"2026-07-05T01:48:35.844700Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:48:35.844700Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2011.01773","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":"2026-07-05T01:48:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FvN8/ZRzXIoLaKQpxF0sIYwwf4tdnEjyFpiYeSGauBZqAlDefeWhywg3dWbq/AWZddWESSky2EB1nYLgZprFDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T15:52:14.602575Z"},"content_sha256":"85c218cd064231a24e3fcf2ef0d72d995becf0e4dc7de0607a7243492b9190f0","schema_version":"1.0","event_id":"sha256:85c218cd064231a24e3fcf2ef0d72d995becf0e4dc7de0607a7243492b9190f0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:6FUR5545RGJMLX2FPAZBLVNR5H","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Memory-Efficient RkNN Retrieval by Nonlinear k-Distance Approximation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"Max Berrendorf, Peer Kr\\\"oger, Sandra Obermeier","submitted_at":"2020-11-03T15:13:05Z","abstract_excerpt":"The reverse k-nearest neighbor (RkNN) query is an established query type with various applications reaching from identifying highly influential objects over incrementally updating kNN graphs to optimizing sensor communication and outlier detection. State-of-the-art solutions exploit that the k-distances in real-world datasets often follow the power-law distribution, and bound them with linear lines in log-log space. In this work, we investigate this assumption and uncover that it is violated in regions of changing density, which we show are typical for real-life datasets. Towards a generic sol"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.01773","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2011.01773/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:48:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7TrwF5A0NHRbgoIx6iwVo4X5Ocg6JE47A0RxlzY8kIrywpim41XRUxl09wHBbEvv73Qz5QdcPA3dqs5tzU8gAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T15:52:14.603213Z"},"content_sha256":"7fd3ef995293206693902c989561e409b25844376a82da14a4a16bd564636df8","schema_version":"1.0","event_id":"sha256:7fd3ef995293206693902c989561e409b25844376a82da14a4a16bd564636df8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6FUR5545RGJMLX2FPAZBLVNR5H/bundle.json","state_url":"https://pith.science/pith/6FUR5545RGJMLX2FPAZBLVNR5H/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6FUR5545RGJMLX2FPAZBLVNR5H/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":"2026-08-14T15:52:14Z","links":{"resolver":"https://pith.science/pith/6FUR5545RGJMLX2FPAZBLVNR5H","bundle":"https://pith.science/pith/6FUR5545RGJMLX2FPAZBLVNR5H/bundle.json","state":"https://pith.science/pith/6FUR5545RGJMLX2FPAZBLVNR5H/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6FUR5545RGJMLX2FPAZBLVNR5H/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:6FUR5545RGJMLX2FPAZBLVNR5H","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":"bace1d779906a30d6a8b77cb9fa6b2735584feec4018eaf95be1ad4af43fc2ff","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2020-11-03T15:13:05Z","title_canon_sha256":"6d4e0de7d33ffe1ead7eb87fad49fe59bcb2aec7c287b20cae965309fdac9f7f"},"schema_version":"1.0","source":{"id":"2011.01773","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.01773","created_at":"2026-07-05T01:48:35Z"},{"alias_kind":"arxiv_version","alias_value":"2011.01773v1","created_at":"2026-07-05T01:48:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.01773","created_at":"2026-07-05T01:48:35Z"},{"alias_kind":"pith_short_12","alias_value":"6FUR5545RGJM","created_at":"2026-07-05T01:48:35Z"},{"alias_kind":"pith_short_16","alias_value":"6FUR5545RGJMLX2F","created_at":"2026-07-05T01:48:35Z"},{"alias_kind":"pith_short_8","alias_value":"6FUR5545","created_at":"2026-07-05T01:48:35Z"}],"graph_snapshots":[{"event_id":"sha256:7fd3ef995293206693902c989561e409b25844376a82da14a4a16bd564636df8","target":"graph","created_at":"2026-07-05T01:48:35Z","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/2011.01773/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The reverse k-nearest neighbor (RkNN) query is an established query type with various applications reaching from identifying highly influential objects over incrementally updating kNN graphs to optimizing sensor communication and outlier detection. State-of-the-art solutions exploit that the k-distances in real-world datasets often follow the power-law distribution, and bound them with linear lines in log-log space. In this work, we investigate this assumption and uncover that it is violated in regions of changing density, which we show are typical for real-life datasets. Towards a generic sol","authors_text":"Max Berrendorf, Peer Kr\\\"oger, Sandra Obermeier","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2020-11-03T15:13:05Z","title":"Memory-Efficient RkNN Retrieval by Nonlinear k-Distance Approximation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.01773","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":"sha256:85c218cd064231a24e3fcf2ef0d72d995becf0e4dc7de0607a7243492b9190f0","target":"record","created_at":"2026-07-05T01:48:35Z","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":"bace1d779906a30d6a8b77cb9fa6b2735584feec4018eaf95be1ad4af43fc2ff","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2020-11-03T15:13:05Z","title_canon_sha256":"6d4e0de7d33ffe1ead7eb87fad49fe59bcb2aec7c287b20cae965309fdac9f7f"},"schema_version":"1.0","source":{"id":"2011.01773","kind":"arxiv","version":1}},"canonical_sha256":"f1691ef79d8992c5df45783215d5b1e9ef341018828cdb19a025b9c2ab9765c4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f1691ef79d8992c5df45783215d5b1e9ef341018828cdb19a025b9c2ab9765c4","first_computed_at":"2026-07-05T01:48:35.844700Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:48:35.844700Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PTkYj/vugwcDXc976EGzCs/ZJUztC79mE/rrJyh25+irIxNsLAzEBhTFjh8jdPf3+KW97fruarGEoZVdtm6XBA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:48:35.845144Z","signed_message":"canonical_sha256_bytes"},"source_id":"2011.01773","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:85c218cd064231a24e3fcf2ef0d72d995becf0e4dc7de0607a7243492b9190f0","sha256:7fd3ef995293206693902c989561e409b25844376a82da14a4a16bd564636df8"],"state_sha256":"ea4aa9dbaa98aedeb289935f7c8d2882f195fadd9faa3de16d8e64a29fc0e7ff"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YhWLzI7GT/pPiS15muswizVywjSORNytQdy9ox0xgmQu3/bKoxdHSOrYHiDSzza3qyq9VyoC87Ao8B92AwavAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T15:52:14.607873Z","bundle_sha256":"079d12f9f0a41af34c967c7ec8ac2463bb1551d52aea2329531e10e9e4c1370e"}}