{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:S5O22YKELB2P3UUJH2IK6OEYOO","short_pith_number":"pith:S5O22YKE","canonical_record":{"source":{"id":"1710.09085","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-10-25T06:26:28Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"29fa6ac4dcd87473191650efad10a349f861204f8b5597047a05640705f68ef2","abstract_canon_sha256":"41221c226b2ef1bf1da83476c41e566bfebaf77963f970c588f890fd696062b7"},"schema_version":"1.0"},"canonical_sha256":"975dad61445874fdd2893e90af38987381390c7fde572e5b283fbe54b461d95e","source":{"kind":"arxiv","id":"1710.09085","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.09085","created_at":"2026-05-18T00:32:00Z"},{"alias_kind":"arxiv_version","alias_value":"1710.09085v1","created_at":"2026-05-18T00:32:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.09085","created_at":"2026-05-18T00:32:00Z"},{"alias_kind":"pith_short_12","alias_value":"S5O22YKELB2P","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"S5O22YKELB2P3UUJ","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"S5O22YKE","created_at":"2026-05-18T12:31:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:S5O22YKELB2P3UUJH2IK6OEYOO","target":"record","payload":{"canonical_record":{"source":{"id":"1710.09085","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-10-25T06:26:28Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"29fa6ac4dcd87473191650efad10a349f861204f8b5597047a05640705f68ef2","abstract_canon_sha256":"41221c226b2ef1bf1da83476c41e566bfebaf77963f970c588f890fd696062b7"},"schema_version":"1.0"},"canonical_sha256":"975dad61445874fdd2893e90af38987381390c7fde572e5b283fbe54b461d95e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:32:00.409766Z","signature_b64":"TghLZZFFi9S+4HVPGedT8WBpoPEJIOc4P0z8Cg1/uDUcgn88R+2iwi4QfnF0RRH7z3uk7YNtEXlnxFgca+vXCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"975dad61445874fdd2893e90af38987381390c7fde572e5b283fbe54b461d95e","last_reissued_at":"2026-05-18T00:32:00.409263Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:32:00.409263Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1710.09085","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":"2026-05-18T00:32:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/kTJNk1a5RmQ2hyUA0a918DTQwqknzhlsmx7mKMQnbP5Ibz2ojw1ImKo329xbOLLsNfPj7PjEuS+QPODYEUBDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T06:03:36.267873Z"},"content_sha256":"4a5b05b3e5fe20913841f53508a565e75bd58aefea2e6154a659dd6466b79af9","schema_version":"1.0","event_id":"sha256:4a5b05b3e5fe20913841f53508a565e75bd58aefea2e6154a659dd6466b79af9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:S5O22YKELB2P3UUJH2IK6OEYOO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Re-evaluating the need for Modelling Term-Dependence in Text Classification Problems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.IR","authors_text":"Mandar Mitra, Prasenjit Majumder, Sounak Banerjee","submitted_at":"2017-10-25T06:26:28Z","abstract_excerpt":"A substantial amount of research has been carried out in developing machine learning algorithms that account for term dependence in text classification. These algorithms offer acceptable performance in most cases but they are associated with a substantial cost. They require significantly greater resources to operate. This paper argues against the justification of the higher costs of these algorithms, based on their performance in text classification problems. In order to prove the conjecture, the performance of one of the best dependence models is compared to several well established algorithm"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.09085","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":"2026-05-18T00:32:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ShqM0aAudkcmxfyV3/kOApRiKY8s8e9H6VZHEjJpz1YQ3DRV1VxYg1QUPKMi/zGljVJNtIDf6OYYxqpn/zVFBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T06:03:36.268575Z"},"content_sha256":"d823b72e762b3dbae24d7ec0786b7988bf564c626f606424f6900cf5d3e0dc4c","schema_version":"1.0","event_id":"sha256:d823b72e762b3dbae24d7ec0786b7988bf564c626f606424f6900cf5d3e0dc4c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/S5O22YKELB2P3UUJH2IK6OEYOO/bundle.json","state_url":"https://pith.science/pith/S5O22YKELB2P3UUJH2IK6OEYOO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/S5O22YKELB2P3UUJH2IK6OEYOO/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":"2026-05-25T06:03:36Z","links":{"resolver":"https://pith.science/pith/S5O22YKELB2P3UUJH2IK6OEYOO","bundle":"https://pith.science/pith/S5O22YKELB2P3UUJH2IK6OEYOO/bundle.json","state":"https://pith.science/pith/S5O22YKELB2P3UUJH2IK6OEYOO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/S5O22YKELB2P3UUJH2IK6OEYOO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:S5O22YKELB2P3UUJH2IK6OEYOO","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":"41221c226b2ef1bf1da83476c41e566bfebaf77963f970c588f890fd696062b7","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-10-25T06:26:28Z","title_canon_sha256":"29fa6ac4dcd87473191650efad10a349f861204f8b5597047a05640705f68ef2"},"schema_version":"1.0","source":{"id":"1710.09085","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.09085","created_at":"2026-05-18T00:32:00Z"},{"alias_kind":"arxiv_version","alias_value":"1710.09085v1","created_at":"2026-05-18T00:32:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.09085","created_at":"2026-05-18T00:32:00Z"},{"alias_kind":"pith_short_12","alias_value":"S5O22YKELB2P","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"S5O22YKELB2P3UUJ","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"S5O22YKE","created_at":"2026-05-18T12:31:43Z"}],"graph_snapshots":[{"event_id":"sha256:d823b72e762b3dbae24d7ec0786b7988bf564c626f606424f6900cf5d3e0dc4c","target":"graph","created_at":"2026-05-18T00:32:00Z","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":"A substantial amount of research has been carried out in developing machine learning algorithms that account for term dependence in text classification. These algorithms offer acceptable performance in most cases but they are associated with a substantial cost. They require significantly greater resources to operate. This paper argues against the justification of the higher costs of these algorithms, based on their performance in text classification problems. In order to prove the conjecture, the performance of one of the best dependence models is compared to several well established algorithm","authors_text":"Mandar Mitra, Prasenjit Majumder, Sounak Banerjee","cross_cats":["cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-10-25T06:26:28Z","title":"Re-evaluating the need for Modelling Term-Dependence in Text Classification Problems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.09085","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":"sha256:4a5b05b3e5fe20913841f53508a565e75bd58aefea2e6154a659dd6466b79af9","target":"record","created_at":"2026-05-18T00:32:00Z","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":"41221c226b2ef1bf1da83476c41e566bfebaf77963f970c588f890fd696062b7","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-10-25T06:26:28Z","title_canon_sha256":"29fa6ac4dcd87473191650efad10a349f861204f8b5597047a05640705f68ef2"},"schema_version":"1.0","source":{"id":"1710.09085","kind":"arxiv","version":1}},"canonical_sha256":"975dad61445874fdd2893e90af38987381390c7fde572e5b283fbe54b461d95e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"975dad61445874fdd2893e90af38987381390c7fde572e5b283fbe54b461d95e","first_computed_at":"2026-05-18T00:32:00.409263Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:32:00.409263Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TghLZZFFi9S+4HVPGedT8WBpoPEJIOc4P0z8Cg1/uDUcgn88R+2iwi4QfnF0RRH7z3uk7YNtEXlnxFgca+vXCw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:32:00.409766Z","signed_message":"canonical_sha256_bytes"},"source_id":"1710.09085","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4a5b05b3e5fe20913841f53508a565e75bd58aefea2e6154a659dd6466b79af9","sha256:d823b72e762b3dbae24d7ec0786b7988bf564c626f606424f6900cf5d3e0dc4c"],"state_sha256":"2d251c8700532b757529362c739cc93b13f1ed840c0b318e9ff49338efd517b6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hQoyNgPiI5o7Bdu18fnt/qADpx88hKb309AtqudvL8XhhL/HhUoHQbn+YbpkVhKGJh/E15xpOGDs4ve85MRqBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T06:03:36.272523Z","bundle_sha256":"a38f44c708116a42f97d4d513028b422c3092ae6bf8171a83fd09abccbc1f547"}}