{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:KSP37QVUCJJPSYBSOT3DOQBWIX","short_pith_number":"pith:KSP37QVU","canonical_record":{"source":{"id":"1904.08067","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-04-17T03:29:05Z","cross_cats_sorted":["cs.AI","cs.CL","cs.IR","stat.ML"],"title_canon_sha256":"4253696ca5f314fe68892be946cefabed55793005758114014075a57212a94d5","abstract_canon_sha256":"6e0ffe127964ee2ae002c50ee7ea9d96c22701e4d86da1f9baddedfd4f47f950"},"schema_version":"1.0"},"canonical_sha256":"549fbfc2b41252f9603274f637403645f84b23f546a3732eda406fdee6641913","source":{"kind":"arxiv","id":"1904.08067","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.08067","created_at":"2026-07-05T01:04:27Z"},{"alias_kind":"arxiv_version","alias_value":"1904.08067v5","created_at":"2026-07-05T01:04:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.08067","created_at":"2026-07-05T01:04:27Z"},{"alias_kind":"pith_short_12","alias_value":"KSP37QVUCJJP","created_at":"2026-07-05T01:04:27Z"},{"alias_kind":"pith_short_16","alias_value":"KSP37QVUCJJPSYBS","created_at":"2026-07-05T01:04:27Z"},{"alias_kind":"pith_short_8","alias_value":"KSP37QVU","created_at":"2026-07-05T01:04:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:KSP37QVUCJJPSYBSOT3DOQBWIX","target":"record","payload":{"canonical_record":{"source":{"id":"1904.08067","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-04-17T03:29:05Z","cross_cats_sorted":["cs.AI","cs.CL","cs.IR","stat.ML"],"title_canon_sha256":"4253696ca5f314fe68892be946cefabed55793005758114014075a57212a94d5","abstract_canon_sha256":"6e0ffe127964ee2ae002c50ee7ea9d96c22701e4d86da1f9baddedfd4f47f950"},"schema_version":"1.0"},"canonical_sha256":"549fbfc2b41252f9603274f637403645f84b23f546a3732eda406fdee6641913","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:04:27.781900Z","signature_b64":"5IGiKUxt61eDkf/9jEJcx2Z5EaDNK6Q8KMAcEa/DWRblb1fYwx5nb74WX7Un5wUXwcPySdJYNLCvC0bxAUp0Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"549fbfc2b41252f9603274f637403645f84b23f546a3732eda406fdee6641913","last_reissued_at":"2026-07-05T01:04:27.781397Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:04:27.781397Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.08067","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:04:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wh7KVuZMYPMQap/OrmcqApktYSet3cIsAyeZMyel0Jzej+GOyT+jOR0O4oABPtXbPcWm7AR3w8tWpUztOF3hCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T02:24:16.673378Z"},"content_sha256":"cbea923a8ad5455d4bdbd552c761ba2141ebda02a00bfe66439e577729520283","schema_version":"1.0","event_id":"sha256:cbea923a8ad5455d4bdbd552c761ba2141ebda02a00bfe66439e577729520283"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:KSP37QVUCJJPSYBSOT3DOQBWIX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Text Classification Algorithms: A Survey","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.IR","stat.ML"],"primary_cat":"cs.LG","authors_text":"Donald E. Brown, Kamran Kowsari, Kiana Jafari Meimandi, Laura E. Barnes, Mojtaba Heidarysafa, Sanjana Mendu","submitted_at":"2019-04-17T03:29:05Z","abstract_excerpt":"In recent years, there has been an exponential growth in the number of complex documents and texts that require a deeper understanding of machine learning methods to be able to accurately classify texts in many applications. Many machine learning approaches have achieved surpassing results in natural language processing. The success of these learning algorithms relies on their capacity to understand complex models and non-linear relationships within data. However, finding suitable structures, architectures, and techniques for text classification is a challenge for researchers. In this paper, a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.08067","kind":"arxiv","version":5},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1904.08067/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T01:04:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Of5tHuw+L2SHO6xxwaTvKOV8PjLM2QHhh5tZdzWcs0GQtEqDV3QpfaTIhkeS0dOwpZsIDqLercIEra1sCs70Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T02:24:16.674282Z"},"content_sha256":"d37a709151a3333a5b0a95d4704cbbbd286351196659e0b5bf9bfd8be3dec386","schema_version":"1.0","event_id":"sha256:d37a709151a3333a5b0a95d4704cbbbd286351196659e0b5bf9bfd8be3dec386"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KSP37QVUCJJPSYBSOT3DOQBWIX/bundle.json","state_url":"https://pith.science/pith/KSP37QVUCJJPSYBSOT3DOQBWIX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KSP37QVUCJJPSYBSOT3DOQBWIX/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":"2026-08-04T02:24:16Z","links":{"resolver":"https://pith.science/pith/KSP37QVUCJJPSYBSOT3DOQBWIX","bundle":"https://pith.science/pith/KSP37QVUCJJPSYBSOT3DOQBWIX/bundle.json","state":"https://pith.science/pith/KSP37QVUCJJPSYBSOT3DOQBWIX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KSP37QVUCJJPSYBSOT3DOQBWIX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:KSP37QVUCJJPSYBSOT3DOQBWIX","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":"6e0ffe127964ee2ae002c50ee7ea9d96c22701e4d86da1f9baddedfd4f47f950","cross_cats_sorted":["cs.AI","cs.CL","cs.IR","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-04-17T03:29:05Z","title_canon_sha256":"4253696ca5f314fe68892be946cefabed55793005758114014075a57212a94d5"},"schema_version":"1.0","source":{"id":"1904.08067","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.08067","created_at":"2026-07-05T01:04:27Z"},{"alias_kind":"arxiv_version","alias_value":"1904.08067v5","created_at":"2026-07-05T01:04:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.08067","created_at":"2026-07-05T01:04:27Z"},{"alias_kind":"pith_short_12","alias_value":"KSP37QVUCJJP","created_at":"2026-07-05T01:04:27Z"},{"alias_kind":"pith_short_16","alias_value":"KSP37QVUCJJPSYBS","created_at":"2026-07-05T01:04:27Z"},{"alias_kind":"pith_short_8","alias_value":"KSP37QVU","created_at":"2026-07-05T01:04:27Z"}],"graph_snapshots":[{"event_id":"sha256:d37a709151a3333a5b0a95d4704cbbbd286351196659e0b5bf9bfd8be3dec386","target":"graph","created_at":"2026-07-05T01:04:27Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1904.08067/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent years, there has been an exponential growth in the number of complex documents and texts that require a deeper understanding of machine learning methods to be able to accurately classify texts in many applications. Many machine learning approaches have achieved surpassing results in natural language processing. The success of these learning algorithms relies on their capacity to understand complex models and non-linear relationships within data. However, finding suitable structures, architectures, and techniques for text classification is a challenge for researchers. In this paper, a","authors_text":"Donald E. Brown, Kamran Kowsari, Kiana Jafari Meimandi, Laura E. Barnes, Mojtaba Heidarysafa, Sanjana Mendu","cross_cats":["cs.AI","cs.CL","cs.IR","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-04-17T03:29:05Z","title":"Text Classification Algorithms: A Survey"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.08067","kind":"arxiv","version":5},"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:cbea923a8ad5455d4bdbd552c761ba2141ebda02a00bfe66439e577729520283","target":"record","created_at":"2026-07-05T01:04:27Z","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":"6e0ffe127964ee2ae002c50ee7ea9d96c22701e4d86da1f9baddedfd4f47f950","cross_cats_sorted":["cs.AI","cs.CL","cs.IR","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-04-17T03:29:05Z","title_canon_sha256":"4253696ca5f314fe68892be946cefabed55793005758114014075a57212a94d5"},"schema_version":"1.0","source":{"id":"1904.08067","kind":"arxiv","version":5}},"canonical_sha256":"549fbfc2b41252f9603274f637403645f84b23f546a3732eda406fdee6641913","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"549fbfc2b41252f9603274f637403645f84b23f546a3732eda406fdee6641913","first_computed_at":"2026-07-05T01:04:27.781397Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:04:27.781397Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5IGiKUxt61eDkf/9jEJcx2Z5EaDNK6Q8KMAcEa/DWRblb1fYwx5nb74WX7Un5wUXwcPySdJYNLCvC0bxAUp0Aw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:04:27.781900Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.08067","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cbea923a8ad5455d4bdbd552c761ba2141ebda02a00bfe66439e577729520283","sha256:d37a709151a3333a5b0a95d4704cbbbd286351196659e0b5bf9bfd8be3dec386"],"state_sha256":"a79879f561ffd32984b84a5bb9ba6a9bc2f5aea825598506aef4e05300442b8a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tWxi39RxAOqsd4Gth+FlmQyNW7y3O4L7gRRueuiRnIwq8QYH1jh2qMliogqwutAiD3/Wljex6gMa/Nx+A3ZDDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T02:24:16.679605Z","bundle_sha256":"5105a61d879d90052cbe1fcfe8cc30011888b2f147762a1dc3ad6583e3efd278"}}