{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:EB6S3H42APYD4F7XCIUTR7TWXA","short_pith_number":"pith:EB6S3H42","canonical_record":{"source":{"id":"1901.01710","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-01-07T08:58:59Z","cross_cats_sorted":["cs.DS"],"title_canon_sha256":"ae92ae5e8140429f6c00edf7125308561817ebf0a0052e1f9510a642b0a53a4a","abstract_canon_sha256":"bddde4042ffd77b2a375d74fc40e889bd92a3334eb10e81b27b07860a84504ad"},"schema_version":"1.0"},"canonical_sha256":"207d2d9f9a03f03e17f7122938fe76b831de900c739b1bbdd915c78e16638a09","source":{"kind":"arxiv","id":"1901.01710","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.01710","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"arxiv_version","alias_value":"1901.01710v1","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.01710","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"pith_short_12","alias_value":"EB6S3H42APYD","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"EB6S3H42APYD4F7X","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"EB6S3H42","created_at":"2026-05-18T12:33:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:EB6S3H42APYD4F7XCIUTR7TWXA","target":"record","payload":{"canonical_record":{"source":{"id":"1901.01710","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-01-07T08:58:59Z","cross_cats_sorted":["cs.DS"],"title_canon_sha256":"ae92ae5e8140429f6c00edf7125308561817ebf0a0052e1f9510a642b0a53a4a","abstract_canon_sha256":"bddde4042ffd77b2a375d74fc40e889bd92a3334eb10e81b27b07860a84504ad"},"schema_version":"1.0"},"canonical_sha256":"207d2d9f9a03f03e17f7122938fe76b831de900c739b1bbdd915c78e16638a09","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:56:51.402369Z","signature_b64":"/RPLq0ImrVhTerVldw/UZg6Bzop5lALdP6GL7Yy4+7YDTElgJ6yUOJpjAoyHAydcqU8Xw1R1RBuRhTwHwgm7BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"207d2d9f9a03f03e17f7122938fe76b831de900c739b1bbdd915c78e16638a09","last_reissued_at":"2026-05-17T23:56:51.401944Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:56:51.401944Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1901.01710","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":"2026-05-17T23:56:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YXYVJeUSQORa5FAxPjEaD7v9LQGg0Y05swruVoivnu/C/RQsV2tKYDtM2Q7f4pZea5+yC9QDSWZmSdSsVWoZDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T01:24:04.179029Z"},"content_sha256":"37b4ab3fadebb92b136324e2b59a496441852e16b9da0d86808ff3e1b2751a66","schema_version":"1.0","event_id":"sha256:37b4ab3fadebb92b136324e2b59a496441852e16b9da0d86808ff3e1b2751a66"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:EB6S3H42APYD4F7XCIUTR7TWXA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Approximate-Closed-Itemset Mining for Streaming Data Under Resource Constraint","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DS"],"primary_cat":"cs.DB","authors_text":"Koji Iwanuma, Yasuo Tabei, Yoshitaka Yamamoto","submitted_at":"2019-01-07T08:58:59Z","abstract_excerpt":"Here, we present a novel algorithm for frequent itemset mining for streaming data (FIM-SD). For the past decade, various FIM-SD methods in one-pass approximation settings have been developed to approximate the frequency of each itemset. These approaches can be categorized into two approximation types: parameter-constrained (PC) mining and resource-constrained (RC) mining. PC methods control the maximum error that can be included in the frequency based on a pre-defined parameter. In contrast, RC methods limit the maximum memory consumption based on resource constraints. However, the existing PC"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.01710","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":"2026-05-17T23:56:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SV5m5Y6kPwK3oCssHE0nGAAVGifgSGcwCP2PXJppvGLvMn45Hz1yDskUzxOF8L3joJs/WxkR/tbtcuO26URNDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T01:24:04.179379Z"},"content_sha256":"06a4f557f4756096c44883b81d1908f0f8a80b96e21b4d2317636466b3bd9170","schema_version":"1.0","event_id":"sha256:06a4f557f4756096c44883b81d1908f0f8a80b96e21b4d2317636466b3bd9170"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EB6S3H42APYD4F7XCIUTR7TWXA/bundle.json","state_url":"https://pith.science/pith/EB6S3H42APYD4F7XCIUTR7TWXA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EB6S3H42APYD4F7XCIUTR7TWXA/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":"2026-06-27T01:24:04Z","links":{"resolver":"https://pith.science/pith/EB6S3H42APYD4F7XCIUTR7TWXA","bundle":"https://pith.science/pith/EB6S3H42APYD4F7XCIUTR7TWXA/bundle.json","state":"https://pith.science/pith/EB6S3H42APYD4F7XCIUTR7TWXA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EB6S3H42APYD4F7XCIUTR7TWXA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:EB6S3H42APYD4F7XCIUTR7TWXA","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":"bddde4042ffd77b2a375d74fc40e889bd92a3334eb10e81b27b07860a84504ad","cross_cats_sorted":["cs.DS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-01-07T08:58:59Z","title_canon_sha256":"ae92ae5e8140429f6c00edf7125308561817ebf0a0052e1f9510a642b0a53a4a"},"schema_version":"1.0","source":{"id":"1901.01710","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.01710","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"arxiv_version","alias_value":"1901.01710v1","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.01710","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"pith_short_12","alias_value":"EB6S3H42APYD","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"EB6S3H42APYD4F7X","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"EB6S3H42","created_at":"2026-05-18T12:33:15Z"}],"graph_snapshots":[{"event_id":"sha256:06a4f557f4756096c44883b81d1908f0f8a80b96e21b4d2317636466b3bd9170","target":"graph","created_at":"2026-05-17T23:56:51Z","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":"Here, we present a novel algorithm for frequent itemset mining for streaming data (FIM-SD). For the past decade, various FIM-SD methods in one-pass approximation settings have been developed to approximate the frequency of each itemset. These approaches can be categorized into two approximation types: parameter-constrained (PC) mining and resource-constrained (RC) mining. PC methods control the maximum error that can be included in the frequency based on a pre-defined parameter. In contrast, RC methods limit the maximum memory consumption based on resource constraints. However, the existing PC","authors_text":"Koji Iwanuma, Yasuo Tabei, Yoshitaka Yamamoto","cross_cats":["cs.DS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-01-07T08:58:59Z","title":"Approximate-Closed-Itemset Mining for Streaming Data Under Resource Constraint"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.01710","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":"sha256:37b4ab3fadebb92b136324e2b59a496441852e16b9da0d86808ff3e1b2751a66","target":"record","created_at":"2026-05-17T23:56:51Z","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":"bddde4042ffd77b2a375d74fc40e889bd92a3334eb10e81b27b07860a84504ad","cross_cats_sorted":["cs.DS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-01-07T08:58:59Z","title_canon_sha256":"ae92ae5e8140429f6c00edf7125308561817ebf0a0052e1f9510a642b0a53a4a"},"schema_version":"1.0","source":{"id":"1901.01710","kind":"arxiv","version":1}},"canonical_sha256":"207d2d9f9a03f03e17f7122938fe76b831de900c739b1bbdd915c78e16638a09","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"207d2d9f9a03f03e17f7122938fe76b831de900c739b1bbdd915c78e16638a09","first_computed_at":"2026-05-17T23:56:51.401944Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:56:51.401944Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/RPLq0ImrVhTerVldw/UZg6Bzop5lALdP6GL7Yy4+7YDTElgJ6yUOJpjAoyHAydcqU8Xw1R1RBuRhTwHwgm7BA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:56:51.402369Z","signed_message":"canonical_sha256_bytes"},"source_id":"1901.01710","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:37b4ab3fadebb92b136324e2b59a496441852e16b9da0d86808ff3e1b2751a66","sha256:06a4f557f4756096c44883b81d1908f0f8a80b96e21b4d2317636466b3bd9170"],"state_sha256":"e4eba4494712471374985200c1bfa6c00df432b82deaa61e29ce79e627098a08"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HIThLCs/n4AmjfiRhLQPC9VpAnjRm0qVTop3dY2rwG9+NiwDTgQPKONf7vi2+ePgU+wUArUpa+vqYV35gjQ0Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T01:24:04.181310Z","bundle_sha256":"8ff2f0f4dbda9307421e6516c7ddecd9178da2bf6698cfc54d84e03a8b310c15"}}