{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:KX5IKHZAXLDMGGACHG6Y5O4Z75","short_pith_number":"pith:KX5IKHZA","canonical_record":{"source":{"id":"1905.08506","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-21T09:08:35Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"ee30713e07ef607a5c7bb2cf3e0d8842f6d187d92e16f7699f37fbfbb5a51bd8","abstract_canon_sha256":"efbae3810922cdc487df55026a5d8e7974d64c972233023dc1560571e9202b2d"},"schema_version":"1.0"},"canonical_sha256":"55fa851f20bac6c3180239bd8ebb99ff7f55a0a1c0e83baed2642854c316fb2b","source":{"kind":"arxiv","id":"1905.08506","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.08506","created_at":"2026-05-17T23:45:43Z"},{"alias_kind":"arxiv_version","alias_value":"1905.08506v1","created_at":"2026-05-17T23:45:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.08506","created_at":"2026-05-17T23:45:43Z"},{"alias_kind":"pith_short_12","alias_value":"KX5IKHZAXLDM","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"KX5IKHZAXLDMGGAC","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"KX5IKHZA","created_at":"2026-05-18T12:33:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:KX5IKHZAXLDMGGACHG6Y5O4Z75","target":"record","payload":{"canonical_record":{"source":{"id":"1905.08506","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-21T09:08:35Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"ee30713e07ef607a5c7bb2cf3e0d8842f6d187d92e16f7699f37fbfbb5a51bd8","abstract_canon_sha256":"efbae3810922cdc487df55026a5d8e7974d64c972233023dc1560571e9202b2d"},"schema_version":"1.0"},"canonical_sha256":"55fa851f20bac6c3180239bd8ebb99ff7f55a0a1c0e83baed2642854c316fb2b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:45:43.009108Z","signature_b64":"qo3QyGc2Tj3CTAF7csusGU5BKUGsLL4wa/fFtMbXIo2oWgG8Uyl5Nzx+MLxMMp3MaftkfjBPoL2GC0oNp3WXBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"55fa851f20bac6c3180239bd8ebb99ff7f55a0a1c0e83baed2642854c316fb2b","last_reissued_at":"2026-05-17T23:45:43.008211Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:45:43.008211Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1905.08506","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":"2026-05-17T23:45:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MudLB0an/P4/gK4iz5SquB6S59/z7585toUztjTsD43JxOQp9C6GNRJqffQG4TTxXPH5HBky/lp9JCjPjJaGDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-03T02:22:20.741924Z"},"content_sha256":"1946f5871688fc70f6a5741acfdf005722d8d75507b1cedd4056f76edb4881a6","schema_version":"1.0","event_id":"sha256:1946f5871688fc70f6a5741acfdf005722d8d75507b1cedd4056f76edb4881a6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:KX5IKHZAXLDMGGACHG6Y5O4Z75","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Data-driven preference learning methods for value-driven multiple criteria sorting with interacting criteria","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Jiapeng Liu, Milosz Kadzinski, Xiaoxin Mao, Xiuwu Liao","submitted_at":"2019-05-21T09:08:35Z","abstract_excerpt":"The learning of predictive models for data-driven decision support has been a prevalent topic in many fields. However, construction of models that would capture interactions among input variables is a challenging task. In this paper, we present a new preference learning approach for multiple criteria sorting with potentially interacting criteria. It employs an additive piecewise-linear value function as the basic preference model, which is augmented with components for handling the interactions. To construct such a model from a given set of assignment examples concerning reference alternatives"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.08506","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":"2026-05-17T23:45:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7H4/bOE0jv1N7KMCroexKP2QsPXUeiDzPF9R2/tR9zD/sOcbFMFjQZ9lO0+OLac4zr5CynHXbW9Rbn7JUIIsAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-03T02:22:20.742261Z"},"content_sha256":"db78855b143bca98cc9dc3fe5fb5445aa65a25a92b41e745031245f3cd0c259c","schema_version":"1.0","event_id":"sha256:db78855b143bca98cc9dc3fe5fb5445aa65a25a92b41e745031245f3cd0c259c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KX5IKHZAXLDMGGACHG6Y5O4Z75/bundle.json","state_url":"https://pith.science/pith/KX5IKHZAXLDMGGACHG6Y5O4Z75/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KX5IKHZAXLDMGGACHG6Y5O4Z75/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":"2026-07-03T02:22:20Z","links":{"resolver":"https://pith.science/pith/KX5IKHZAXLDMGGACHG6Y5O4Z75","bundle":"https://pith.science/pith/KX5IKHZAXLDMGGACHG6Y5O4Z75/bundle.json","state":"https://pith.science/pith/KX5IKHZAXLDMGGACHG6Y5O4Z75/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KX5IKHZAXLDMGGACHG6Y5O4Z75/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:KX5IKHZAXLDMGGACHG6Y5O4Z75","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":"efbae3810922cdc487df55026a5d8e7974d64c972233023dc1560571e9202b2d","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-21T09:08:35Z","title_canon_sha256":"ee30713e07ef607a5c7bb2cf3e0d8842f6d187d92e16f7699f37fbfbb5a51bd8"},"schema_version":"1.0","source":{"id":"1905.08506","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.08506","created_at":"2026-05-17T23:45:43Z"},{"alias_kind":"arxiv_version","alias_value":"1905.08506v1","created_at":"2026-05-17T23:45:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.08506","created_at":"2026-05-17T23:45:43Z"},{"alias_kind":"pith_short_12","alias_value":"KX5IKHZAXLDM","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"KX5IKHZAXLDMGGAC","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"KX5IKHZA","created_at":"2026-05-18T12:33:21Z"}],"graph_snapshots":[{"event_id":"sha256:db78855b143bca98cc9dc3fe5fb5445aa65a25a92b41e745031245f3cd0c259c","target":"graph","created_at":"2026-05-17T23:45:43Z","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 learning of predictive models for data-driven decision support has been a prevalent topic in many fields. However, construction of models that would capture interactions among input variables is a challenging task. In this paper, we present a new preference learning approach for multiple criteria sorting with potentially interacting criteria. It employs an additive piecewise-linear value function as the basic preference model, which is augmented with components for handling the interactions. To construct such a model from a given set of assignment examples concerning reference alternatives","authors_text":"Jiapeng Liu, Milosz Kadzinski, Xiaoxin Mao, Xiuwu Liao","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-21T09:08:35Z","title":"Data-driven preference learning methods for value-driven multiple criteria sorting with interacting criteria"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.08506","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":"sha256:1946f5871688fc70f6a5741acfdf005722d8d75507b1cedd4056f76edb4881a6","target":"record","created_at":"2026-05-17T23:45:43Z","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":"efbae3810922cdc487df55026a5d8e7974d64c972233023dc1560571e9202b2d","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-21T09:08:35Z","title_canon_sha256":"ee30713e07ef607a5c7bb2cf3e0d8842f6d187d92e16f7699f37fbfbb5a51bd8"},"schema_version":"1.0","source":{"id":"1905.08506","kind":"arxiv","version":1}},"canonical_sha256":"55fa851f20bac6c3180239bd8ebb99ff7f55a0a1c0e83baed2642854c316fb2b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"55fa851f20bac6c3180239bd8ebb99ff7f55a0a1c0e83baed2642854c316fb2b","first_computed_at":"2026-05-17T23:45:43.008211Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:45:43.008211Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qo3QyGc2Tj3CTAF7csusGU5BKUGsLL4wa/fFtMbXIo2oWgG8Uyl5Nzx+MLxMMp3MaftkfjBPoL2GC0oNp3WXBQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:45:43.009108Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.08506","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1946f5871688fc70f6a5741acfdf005722d8d75507b1cedd4056f76edb4881a6","sha256:db78855b143bca98cc9dc3fe5fb5445aa65a25a92b41e745031245f3cd0c259c"],"state_sha256":"3ed99fb695cb11b93e1468341f6bc49247844b6d19723e2f62cff8c12cee5db9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oU8Tmf7S6/CHoCpkuYL+mJ2NEdjYfNPi0ceBeOUPa4Hl14zd3YH6OueylIEf7XiU3S11ETzxrs9fcRUSNLqkAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-03T02:22:20.744140Z","bundle_sha256":"29d49edc861c497694c086f73325f20a564d46555c241904323a3395bbbdcb98"}}