{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:7AOS2KFB2YBUSBUYVPM5OJJIQR","short_pith_number":"pith:7AOS2KFB","canonical_record":{"source":{"id":"1503.03238","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-03-11T09:38:49Z","cross_cats_sorted":[],"title_canon_sha256":"0d48cf89491d360bc858d0cb0fbcd3cec413aa9fa31fdf2254d04a39c8ca8fd9","abstract_canon_sha256":"c3f16c7cd4cff1e8f98f61568d5e76554c3444c28a4b1a046013677af2d03e54"},"schema_version":"1.0"},"canonical_sha256":"f81d2d28a1d603490698abd9d725288475625d9805b682db2095e865c09d4f4d","source":{"kind":"arxiv","id":"1503.03238","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1503.03238","created_at":"2026-05-18T02:25:04Z"},{"alias_kind":"arxiv_version","alias_value":"1503.03238v1","created_at":"2026-05-18T02:25:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1503.03238","created_at":"2026-05-18T02:25:04Z"},{"alias_kind":"pith_short_12","alias_value":"7AOS2KFB2YBU","created_at":"2026-05-18T12:29:07Z"},{"alias_kind":"pith_short_16","alias_value":"7AOS2KFB2YBUSBUY","created_at":"2026-05-18T12:29:07Z"},{"alias_kind":"pith_short_8","alias_value":"7AOS2KFB","created_at":"2026-05-18T12:29:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:7AOS2KFB2YBUSBUYVPM5OJJIQR","target":"record","payload":{"canonical_record":{"source":{"id":"1503.03238","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-03-11T09:38:49Z","cross_cats_sorted":[],"title_canon_sha256":"0d48cf89491d360bc858d0cb0fbcd3cec413aa9fa31fdf2254d04a39c8ca8fd9","abstract_canon_sha256":"c3f16c7cd4cff1e8f98f61568d5e76554c3444c28a4b1a046013677af2d03e54"},"schema_version":"1.0"},"canonical_sha256":"f81d2d28a1d603490698abd9d725288475625d9805b682db2095e865c09d4f4d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:25:04.023602Z","signature_b64":"VDeUqJlHkQX6HGh1zLoawfRirxqYTmM97MOliWrlct48Ix0bPuHI2iR+kkXjGgQUNXIkrWBLvVhHzUAMnAknBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f81d2d28a1d603490698abd9d725288475625d9805b682db2095e865c09d4f4d","last_reissued_at":"2026-05-18T02:25:04.023241Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:25:04.023241Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1503.03238","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":"2026-05-18T02:25:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4PJRxL732ka8TeJDLCNQ4zV1C1tWKEfiv3ug14uk8wX+GQvBYQgfSANVq9QVaxAQDFbsPDl+fdn+12fHPE0VDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T13:29:40.438890Z"},"content_sha256":"7ea8aba5dd220c72ff99dd047347eb9734ed1629d4118099d28b472e4ad7ca2b","schema_version":"1.0","event_id":"sha256:7ea8aba5dd220c72ff99dd047347eb9734ed1629d4118099d28b472e4ad7ca2b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:7AOS2KFB2YBUSBUYVPM5OJJIQR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Scalable Discovery of Time-Series Shapelets","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Josif Grabocka, Lars Schmidt-Thieme, Martin Wistuba","submitted_at":"2015-03-11T09:38:49Z","abstract_excerpt":"Time-series classification is an important problem for the data mining community due to the wide range of application domains involving time-series data. A recent paradigm, called shapelets, represents patterns that are highly predictive for the target variable. Shapelets are discovered by measuring the prediction accuracy of a set of potential (shapelet) candidates. The candidates typically consist of all the segments of a dataset, therefore, the discovery of shapelets is computationally expensive. This paper proposes a novel method that avoids measuring the prediction accuracy of similar can"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1503.03238","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":"2026-05-18T02:25:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xcW4ihxxetyX3W59xVYzfFhWH4Livhy2boWe7FM02nnJRojTQeKx8i897EqzO6JztxXgVtLeSjCe9ZysUN8BAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T13:29:40.439240Z"},"content_sha256":"543b6fe7fd762f7c8159c135f645e71dabcdde27eccf90734e07641795d6f00b","schema_version":"1.0","event_id":"sha256:543b6fe7fd762f7c8159c135f645e71dabcdde27eccf90734e07641795d6f00b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7AOS2KFB2YBUSBUYVPM5OJJIQR/bundle.json","state_url":"https://pith.science/pith/7AOS2KFB2YBUSBUYVPM5OJJIQR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7AOS2KFB2YBUSBUYVPM5OJJIQR/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":"2026-05-21T13:29:40Z","links":{"resolver":"https://pith.science/pith/7AOS2KFB2YBUSBUYVPM5OJJIQR","bundle":"https://pith.science/pith/7AOS2KFB2YBUSBUYVPM5OJJIQR/bundle.json","state":"https://pith.science/pith/7AOS2KFB2YBUSBUYVPM5OJJIQR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7AOS2KFB2YBUSBUYVPM5OJJIQR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:7AOS2KFB2YBUSBUYVPM5OJJIQR","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":"c3f16c7cd4cff1e8f98f61568d5e76554c3444c28a4b1a046013677af2d03e54","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-03-11T09:38:49Z","title_canon_sha256":"0d48cf89491d360bc858d0cb0fbcd3cec413aa9fa31fdf2254d04a39c8ca8fd9"},"schema_version":"1.0","source":{"id":"1503.03238","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1503.03238","created_at":"2026-05-18T02:25:04Z"},{"alias_kind":"arxiv_version","alias_value":"1503.03238v1","created_at":"2026-05-18T02:25:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1503.03238","created_at":"2026-05-18T02:25:04Z"},{"alias_kind":"pith_short_12","alias_value":"7AOS2KFB2YBU","created_at":"2026-05-18T12:29:07Z"},{"alias_kind":"pith_short_16","alias_value":"7AOS2KFB2YBUSBUY","created_at":"2026-05-18T12:29:07Z"},{"alias_kind":"pith_short_8","alias_value":"7AOS2KFB","created_at":"2026-05-18T12:29:07Z"}],"graph_snapshots":[{"event_id":"sha256:543b6fe7fd762f7c8159c135f645e71dabcdde27eccf90734e07641795d6f00b","target":"graph","created_at":"2026-05-18T02:25:04Z","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":"Time-series classification is an important problem for the data mining community due to the wide range of application domains involving time-series data. A recent paradigm, called shapelets, represents patterns that are highly predictive for the target variable. Shapelets are discovered by measuring the prediction accuracy of a set of potential (shapelet) candidates. The candidates typically consist of all the segments of a dataset, therefore, the discovery of shapelets is computationally expensive. This paper proposes a novel method that avoids measuring the prediction accuracy of similar can","authors_text":"Josif Grabocka, Lars Schmidt-Thieme, Martin Wistuba","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-03-11T09:38:49Z","title":"Scalable Discovery of Time-Series Shapelets"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1503.03238","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":"sha256:7ea8aba5dd220c72ff99dd047347eb9734ed1629d4118099d28b472e4ad7ca2b","target":"record","created_at":"2026-05-18T02:25:04Z","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":"c3f16c7cd4cff1e8f98f61568d5e76554c3444c28a4b1a046013677af2d03e54","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-03-11T09:38:49Z","title_canon_sha256":"0d48cf89491d360bc858d0cb0fbcd3cec413aa9fa31fdf2254d04a39c8ca8fd9"},"schema_version":"1.0","source":{"id":"1503.03238","kind":"arxiv","version":1}},"canonical_sha256":"f81d2d28a1d603490698abd9d725288475625d9805b682db2095e865c09d4f4d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f81d2d28a1d603490698abd9d725288475625d9805b682db2095e865c09d4f4d","first_computed_at":"2026-05-18T02:25:04.023241Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:25:04.023241Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VDeUqJlHkQX6HGh1zLoawfRirxqYTmM97MOliWrlct48Ix0bPuHI2iR+kkXjGgQUNXIkrWBLvVhHzUAMnAknBg==","signature_status":"signed_v1","signed_at":"2026-05-18T02:25:04.023602Z","signed_message":"canonical_sha256_bytes"},"source_id":"1503.03238","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7ea8aba5dd220c72ff99dd047347eb9734ed1629d4118099d28b472e4ad7ca2b","sha256:543b6fe7fd762f7c8159c135f645e71dabcdde27eccf90734e07641795d6f00b"],"state_sha256":"9328d7807e9fceb120d32dcecf0577027e13ec0b2c324a6798613be4069daec0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UnQXZENJIKOIBPAdOoxmcQeDU8TUP8+jQpeEbbNKUVyLJHx5VRrEWy31JJnRmGBRcwDt3HHYK9EC9eS2S8ekBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-21T13:29:40.441441Z","bundle_sha256":"7ad012303e8ec21438ed99bc1e2a894f27ce9fa6c3df8901b75aaf6f59985d15"}}