{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:GDNQP7V3QFJHMQWWQSFEM6G33M","short_pith_number":"pith:GDNQP7V3","canonical_record":{"source":{"id":"1902.02392","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2019-02-06T20:38:24Z","cross_cats_sorted":["cs.DB"],"title_canon_sha256":"c15c4bc42ea9721f3d4549e457eefd72e441609edae93f94078a70c90f9777a7","abstract_canon_sha256":"aec993a2bd6ebbad17d5d998d21f5871d2191a3c6a59ba19229b915b8235ffc3"},"schema_version":"1.0"},"canonical_sha256":"30db07febb81527642d6848a4678dbdb0993e9829f1cf1a0fbe153d018ec2311","source":{"kind":"arxiv","id":"1902.02392","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.02392","created_at":"2026-05-17T23:54:33Z"},{"alias_kind":"arxiv_version","alias_value":"1902.02392v1","created_at":"2026-05-17T23:54:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.02392","created_at":"2026-05-17T23:54:33Z"},{"alias_kind":"pith_short_12","alias_value":"GDNQP7V3QFJH","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_16","alias_value":"GDNQP7V3QFJHMQWW","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_8","alias_value":"GDNQP7V3","created_at":"2026-05-18T12:33:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:GDNQP7V3QFJHMQWWQSFEM6G33M","target":"record","payload":{"canonical_record":{"source":{"id":"1902.02392","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2019-02-06T20:38:24Z","cross_cats_sorted":["cs.DB"],"title_canon_sha256":"c15c4bc42ea9721f3d4549e457eefd72e441609edae93f94078a70c90f9777a7","abstract_canon_sha256":"aec993a2bd6ebbad17d5d998d21f5871d2191a3c6a59ba19229b915b8235ffc3"},"schema_version":"1.0"},"canonical_sha256":"30db07febb81527642d6848a4678dbdb0993e9829f1cf1a0fbe153d018ec2311","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:54:33.543514Z","signature_b64":"4Sj82tX9w0UsxhWqIjZbQ5A9G3DB4/Zg9wgiyhCmQ59ZKVjqA3pSWEk4CoAHARx02fIEiM8B+4EdCt4YL2ZeDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"30db07febb81527642d6848a4678dbdb0993e9829f1cf1a0fbe153d018ec2311","last_reissued_at":"2026-05-17T23:54:33.542788Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:54:33.542788Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1902.02392","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":"2026-05-17T23:54:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3Dm1wxTr7DY9sTTWc2uL2Ok2lzRB6MfrYuTQHObIJc+FUCKCKhuttMbvRj+hspkjiHlx122Lqwy9F/ULXi58Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T14:39:49.591108Z"},"content_sha256":"16600336d1bc5aa955fc717623e871f7f53ae213d9dd34935b8e0f2a80b48ae4","schema_version":"1.0","event_id":"sha256:16600336d1bc5aa955fc717623e871f7f53ae213d9dd34935b8e0f2a80b48ae4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:GDNQP7V3QFJHMQWWQSFEM6G33M","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Finding Good Itemsets by Packing Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DB"],"primary_cat":"cs.DS","authors_text":"Jilles Vreeken, Nikolaj Tatti","submitted_at":"2019-02-06T20:38:24Z","abstract_excerpt":"The problem of selecting small groups of itemsets that represent the data well has recently gained a lot of attention. We approach the problem by searching for the itemsets that compress the data efficiently. As a compression technique we use decision trees combined with a refined version of MDL. More formally, assuming that the items are ordered, we create a decision tree for each item that may only depend on the previous items. Our approach allows us to find complex interactions between the attributes, not just co-occurrences of 1s. Further, we present a link between the itemsets and the dec"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.02392","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":"2026-05-17T23:54:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wfdDeDe/7tOcXQ8149UmQ/1sgz1fHOuTm23mefVJfnBqVwyc9P7DJoAZRuzS4LXfuMU9E67cNMGYrOCgnex7CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T14:39:49.591901Z"},"content_sha256":"4b59c96491d7ea1e8d6b9826c75a8d1fcdab97e1115b943427f80c743de2a868","schema_version":"1.0","event_id":"sha256:4b59c96491d7ea1e8d6b9826c75a8d1fcdab97e1115b943427f80c743de2a868"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GDNQP7V3QFJHMQWWQSFEM6G33M/bundle.json","state_url":"https://pith.science/pith/GDNQP7V3QFJHMQWWQSFEM6G33M/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GDNQP7V3QFJHMQWWQSFEM6G33M/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":"2026-05-26T14:39:49Z","links":{"resolver":"https://pith.science/pith/GDNQP7V3QFJHMQWWQSFEM6G33M","bundle":"https://pith.science/pith/GDNQP7V3QFJHMQWWQSFEM6G33M/bundle.json","state":"https://pith.science/pith/GDNQP7V3QFJHMQWWQSFEM6G33M/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GDNQP7V3QFJHMQWWQSFEM6G33M/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:GDNQP7V3QFJHMQWWQSFEM6G33M","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":"aec993a2bd6ebbad17d5d998d21f5871d2191a3c6a59ba19229b915b8235ffc3","cross_cats_sorted":["cs.DB"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2019-02-06T20:38:24Z","title_canon_sha256":"c15c4bc42ea9721f3d4549e457eefd72e441609edae93f94078a70c90f9777a7"},"schema_version":"1.0","source":{"id":"1902.02392","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.02392","created_at":"2026-05-17T23:54:33Z"},{"alias_kind":"arxiv_version","alias_value":"1902.02392v1","created_at":"2026-05-17T23:54:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.02392","created_at":"2026-05-17T23:54:33Z"},{"alias_kind":"pith_short_12","alias_value":"GDNQP7V3QFJH","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_16","alias_value":"GDNQP7V3QFJHMQWW","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_8","alias_value":"GDNQP7V3","created_at":"2026-05-18T12:33:18Z"}],"graph_snapshots":[{"event_id":"sha256:4b59c96491d7ea1e8d6b9826c75a8d1fcdab97e1115b943427f80c743de2a868","target":"graph","created_at":"2026-05-17T23:54:33Z","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":"The problem of selecting small groups of itemsets that represent the data well has recently gained a lot of attention. We approach the problem by searching for the itemsets that compress the data efficiently. As a compression technique we use decision trees combined with a refined version of MDL. More formally, assuming that the items are ordered, we create a decision tree for each item that may only depend on the previous items. Our approach allows us to find complex interactions between the attributes, not just co-occurrences of 1s. Further, we present a link between the itemsets and the dec","authors_text":"Jilles Vreeken, Nikolaj Tatti","cross_cats":["cs.DB"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2019-02-06T20:38:24Z","title":"Finding Good Itemsets by Packing Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.02392","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":"sha256:16600336d1bc5aa955fc717623e871f7f53ae213d9dd34935b8e0f2a80b48ae4","target":"record","created_at":"2026-05-17T23:54:33Z","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":"aec993a2bd6ebbad17d5d998d21f5871d2191a3c6a59ba19229b915b8235ffc3","cross_cats_sorted":["cs.DB"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2019-02-06T20:38:24Z","title_canon_sha256":"c15c4bc42ea9721f3d4549e457eefd72e441609edae93f94078a70c90f9777a7"},"schema_version":"1.0","source":{"id":"1902.02392","kind":"arxiv","version":1}},"canonical_sha256":"30db07febb81527642d6848a4678dbdb0993e9829f1cf1a0fbe153d018ec2311","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"30db07febb81527642d6848a4678dbdb0993e9829f1cf1a0fbe153d018ec2311","first_computed_at":"2026-05-17T23:54:33.542788Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:54:33.542788Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4Sj82tX9w0UsxhWqIjZbQ5A9G3DB4/Zg9wgiyhCmQ59ZKVjqA3pSWEk4CoAHARx02fIEiM8B+4EdCt4YL2ZeDA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:54:33.543514Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.02392","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:16600336d1bc5aa955fc717623e871f7f53ae213d9dd34935b8e0f2a80b48ae4","sha256:4b59c96491d7ea1e8d6b9826c75a8d1fcdab97e1115b943427f80c743de2a868"],"state_sha256":"127bbd487a72a230f8bcb1d5f330bf000960d7359ed42066e53ec884a6bd931c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"19VJ0IwJUcZO9joEy1Az1wMIJ5JZuz8RITcHUUTVXZSGLvWIOcYmiVpIFfAB3rt+OkmWyMhkLSZoRNAbzLS3AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T14:39:49.596095Z","bundle_sha256":"faa5dfa63e01a643cfeeb4052bebbfc726166b725288f9a300fb905a076cd6ed"}}