{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:3CPZH3OPOLLFYJHYIGFYTNM3AK","short_pith_number":"pith:3CPZH3OP","canonical_record":{"source":{"id":"1907.11803","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-07-26T22:17:07Z","cross_cats_sorted":[],"title_canon_sha256":"bca3e389de93b8fd32c38e27feeb4f99a07333d102eb02911356259f984148c7","abstract_canon_sha256":"7ff0735b538f895753c7f543e183cb5855ab4e86ffc565f57fd36d45a46225c4"},"schema_version":"1.0"},"canonical_sha256":"d89f93edcf72d65c24f8418b89b59b02b5ecdf83d3f45d1568e8e446a9def8f1","source":{"kind":"arxiv","id":"1907.11803","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.11803","created_at":"2026-05-17T23:39:23Z"},{"alias_kind":"arxiv_version","alias_value":"1907.11803v1","created_at":"2026-05-17T23:39:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.11803","created_at":"2026-05-17T23:39:23Z"},{"alias_kind":"pith_short_12","alias_value":"3CPZH3OPOLLF","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"3CPZH3OPOLLFYJHY","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"3CPZH3OP","created_at":"2026-05-18T12:33:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:3CPZH3OPOLLFYJHYIGFYTNM3AK","target":"record","payload":{"canonical_record":{"source":{"id":"1907.11803","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-07-26T22:17:07Z","cross_cats_sorted":[],"title_canon_sha256":"bca3e389de93b8fd32c38e27feeb4f99a07333d102eb02911356259f984148c7","abstract_canon_sha256":"7ff0735b538f895753c7f543e183cb5855ab4e86ffc565f57fd36d45a46225c4"},"schema_version":"1.0"},"canonical_sha256":"d89f93edcf72d65c24f8418b89b59b02b5ecdf83d3f45d1568e8e446a9def8f1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:39:23.004155Z","signature_b64":"q/p9C4soizBiO7XiTiqTW8Bq+TmBmLPSrdkQUPFbX1l5yWnwbZBjdVbI6yAd1rfnASFzY5vmMOQqy9eDhqW2Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d89f93edcf72d65c24f8418b89b59b02b5ecdf83d3f45d1568e8e446a9def8f1","last_reissued_at":"2026-05-17T23:39:23.003480Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:39:23.003480Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.11803","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":"2026-05-17T23:39:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+1yUYnNLUWc++sjk5RjCUqJnRLoSPgdp05sY+vinLICrnex2wle/kmP1F1/wVD9+stA99vNEjZnkGMHLZoRgCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-12T01:03:56.784776Z"},"content_sha256":"f7b5529889a7c7e131d39c8657a7fbfb47f06201dbe83ad05cd470bb5e70a196","schema_version":"1.0","event_id":"sha256:f7b5529889a7c7e131d39c8657a7fbfb47f06201dbe83ad05cd470bb5e70a196"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:3CPZH3OPOLLFYJHYIGFYTNM3AK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"qwLSH: Cache-conscious Indexing for Processing Similarity Search Query Workloads in High-Dimensional Spaces","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"John Ossorgin, Omid Jafari, Parth Nagarkar","submitted_at":"2019-07-26T22:17:07Z","abstract_excerpt":"Similarity search queries in high-dimensional spaces are an important type of queries in many domains such as image processing, machine learning, etc. Since exact similarity search indexing techniques suffer from the well-known curse of dimensionality in high-dimensional spaces, approximate search techniques are often utilized instead. Locality Sensitive Hashing (LSH) has been shown to be an effective approximate search method for solving similarity search queries in high-dimensional spaces. Often times, queries in real-world settings arrive as part of a query workload. LSH and its variants ar"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.11803","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":"2026-05-17T23:39:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ic5qZtERB29CqDShjE/e94R829wR5NDXsaoGLJqGqPKS2Fh28XHrpOlB59/gfWkQ5tYlyavpE+zzs6Cf/AolDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-12T01:03:56.785501Z"},"content_sha256":"197b92dcaf37b8f02098e4e20eef9788ad5dc3a096e962f60a1f2e7502885c22","schema_version":"1.0","event_id":"sha256:197b92dcaf37b8f02098e4e20eef9788ad5dc3a096e962f60a1f2e7502885c22"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3CPZH3OPOLLFYJHYIGFYTNM3AK/bundle.json","state_url":"https://pith.science/pith/3CPZH3OPOLLFYJHYIGFYTNM3AK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3CPZH3OPOLLFYJHYIGFYTNM3AK/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":"2026-06-12T01:03:56Z","links":{"resolver":"https://pith.science/pith/3CPZH3OPOLLFYJHYIGFYTNM3AK","bundle":"https://pith.science/pith/3CPZH3OPOLLFYJHYIGFYTNM3AK/bundle.json","state":"https://pith.science/pith/3CPZH3OPOLLFYJHYIGFYTNM3AK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3CPZH3OPOLLFYJHYIGFYTNM3AK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:3CPZH3OPOLLFYJHYIGFYTNM3AK","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":"7ff0735b538f895753c7f543e183cb5855ab4e86ffc565f57fd36d45a46225c4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-07-26T22:17:07Z","title_canon_sha256":"bca3e389de93b8fd32c38e27feeb4f99a07333d102eb02911356259f984148c7"},"schema_version":"1.0","source":{"id":"1907.11803","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.11803","created_at":"2026-05-17T23:39:23Z"},{"alias_kind":"arxiv_version","alias_value":"1907.11803v1","created_at":"2026-05-17T23:39:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.11803","created_at":"2026-05-17T23:39:23Z"},{"alias_kind":"pith_short_12","alias_value":"3CPZH3OPOLLF","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"3CPZH3OPOLLFYJHY","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"3CPZH3OP","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:197b92dcaf37b8f02098e4e20eef9788ad5dc3a096e962f60a1f2e7502885c22","target":"graph","created_at":"2026-05-17T23:39:23Z","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":"Similarity search queries in high-dimensional spaces are an important type of queries in many domains such as image processing, machine learning, etc. Since exact similarity search indexing techniques suffer from the well-known curse of dimensionality in high-dimensional spaces, approximate search techniques are often utilized instead. Locality Sensitive Hashing (LSH) has been shown to be an effective approximate search method for solving similarity search queries in high-dimensional spaces. Often times, queries in real-world settings arrive as part of a query workload. LSH and its variants ar","authors_text":"John Ossorgin, Omid Jafari, Parth Nagarkar","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-07-26T22:17:07Z","title":"qwLSH: Cache-conscious Indexing for Processing Similarity Search Query Workloads in High-Dimensional Spaces"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.11803","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:f7b5529889a7c7e131d39c8657a7fbfb47f06201dbe83ad05cd470bb5e70a196","target":"record","created_at":"2026-05-17T23:39:23Z","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":"7ff0735b538f895753c7f543e183cb5855ab4e86ffc565f57fd36d45a46225c4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-07-26T22:17:07Z","title_canon_sha256":"bca3e389de93b8fd32c38e27feeb4f99a07333d102eb02911356259f984148c7"},"schema_version":"1.0","source":{"id":"1907.11803","kind":"arxiv","version":1}},"canonical_sha256":"d89f93edcf72d65c24f8418b89b59b02b5ecdf83d3f45d1568e8e446a9def8f1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d89f93edcf72d65c24f8418b89b59b02b5ecdf83d3f45d1568e8e446a9def8f1","first_computed_at":"2026-05-17T23:39:23.003480Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:39:23.003480Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"q/p9C4soizBiO7XiTiqTW8Bq+TmBmLPSrdkQUPFbX1l5yWnwbZBjdVbI6yAd1rfnASFzY5vmMOQqy9eDhqW2Aw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:39:23.004155Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.11803","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f7b5529889a7c7e131d39c8657a7fbfb47f06201dbe83ad05cd470bb5e70a196","sha256:197b92dcaf37b8f02098e4e20eef9788ad5dc3a096e962f60a1f2e7502885c22"],"state_sha256":"5f49d9f36e53a2af2424b535417db3dc81078aac458f02ef706b5efbf4b7ff35"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SCsHnA6afpOgYu31u2d50NlMw/y/VkyzZ6zz9+DQ6PzATqUazfiZR5qDWZ9f2+YeT2X/+h6qSjovJMzl3nWkDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-12T01:03:56.790259Z","bundle_sha256":"71fcc887595068d77278ac9e538a0b4471e206223eb85ee0f308fe201124afcb"}}