{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2011:UQSJZCW72S57DHOILHXXLBBC3I","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":"17635b9e975a710a371aa60907669bd1875ba611a4e9d282beb0e865cbec2d02","cross_cats_sorted":["cs.DS","math.PR","stat.ME","stat.OT","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2011-10-07T09:11:35Z","title_canon_sha256":"1354d3c6e4d334088ad4e53726f7f46ce0ca07f2050d6b304d0ab78a6da8de03"},"schema_version":"1.0","source":{"id":"1110.1462","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1110.1462","created_at":"2026-05-18T01:16:01Z"},{"alias_kind":"arxiv_version","alias_value":"1110.1462v1","created_at":"2026-05-18T01:16:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1110.1462","created_at":"2026-05-18T01:16:01Z"},{"alias_kind":"pith_short_12","alias_value":"UQSJZCW72S57","created_at":"2026-05-18T12:26:42Z"},{"alias_kind":"pith_short_16","alias_value":"UQSJZCW72S57DHOI","created_at":"2026-05-18T12:26:42Z"},{"alias_kind":"pith_short_8","alias_value":"UQSJZCW7","created_at":"2026-05-18T12:26:42Z"}],"graph_snapshots":[{"event_id":"sha256:ac4a40dd7f20217cd518524221de6a1ac76ce3b75ef93f4a0aa82f209dae34fc","target":"graph","created_at":"2026-05-18T01:16:01Z","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":"This paper deals with clustering methods based on adaptive distances for histogram data using a dynamic clustering algorithm. Histogram data describes individuals in terms of empirical distributions. These kind of data can be considered as complex descriptions of phenomena observed on complex objects: images, groups of individuals, spatial or temporal variant data, results of queries, environmental data, and so on. The Wasserstein distance is used to compare two histograms. The Wasserstein distance between histograms is constituted by two components: the first based on the means, and the secon","authors_text":"Antonio Irpino, Francisco de AT De Carvalho, Rosanna Verde","cross_cats":["cs.DS","math.PR","stat.ME","stat.OT","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2011-10-07T09:11:35Z","title":"Dynamic Clustering of Histogram Data Based on Adaptive Squared Wasserstein Distances"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1110.1462","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":"sha256:90986455b73783bd9b59e487cd07f6d6a891dc5bb97a7249979f062f09214d46","target":"record","created_at":"2026-05-18T01:16:01Z","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":"17635b9e975a710a371aa60907669bd1875ba611a4e9d282beb0e865cbec2d02","cross_cats_sorted":["cs.DS","math.PR","stat.ME","stat.OT","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2011-10-07T09:11:35Z","title_canon_sha256":"1354d3c6e4d334088ad4e53726f7f46ce0ca07f2050d6b304d0ab78a6da8de03"},"schema_version":"1.0","source":{"id":"1110.1462","kind":"arxiv","version":1}},"canonical_sha256":"a4249c8adfd4bbf19dc859ef758422da11d83dc5e785022615c2f9676bb0e2be","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a4249c8adfd4bbf19dc859ef758422da11d83dc5e785022615c2f9676bb0e2be","first_computed_at":"2026-05-18T01:16:01.266582Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:16:01.266582Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Pa2ceQ9syHIoFFvKs9ZgVNUBuF75iHhrKfdmB8vpYIksOQcYA8p9DYbkFuDByl5mp8R2SSIxg1yY+K1EpiUYBw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:16:01.267097Z","signed_message":"canonical_sha256_bytes"},"source_id":"1110.1462","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:90986455b73783bd9b59e487cd07f6d6a891dc5bb97a7249979f062f09214d46","sha256:ac4a40dd7f20217cd518524221de6a1ac76ce3b75ef93f4a0aa82f209dae34fc"],"state_sha256":"f0fa3beeafa122d5995d9a37fe4e36d3bb917a19eab1a340a368d66d1db38f6b"}