{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:XP7EGWRUKJXCIXWK3TGQYB242I","short_pith_number":"pith:XP7EGWRU","canonical_record":{"source":{"id":"1706.07913","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-24T06:08:27Z","cross_cats_sorted":["cs.CL","cs.IR"],"title_canon_sha256":"91de8ceed584c316b3f0f81affc5abda29980fd7e975f9ec592da46997c89a36","abstract_canon_sha256":"32cd264c7bed9b162b42555b7aea9deb242b11e6bc27ec194cca2c968bdfe6aa"},"schema_version":"1.0"},"canonical_sha256":"bbfe435a34526e245ecadccd0c075cd20793d8dca54f021fb7476c79e59a18cb","source":{"kind":"arxiv","id":"1706.07913","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1706.07913","created_at":"2026-05-18T00:41:47Z"},{"alias_kind":"arxiv_version","alias_value":"1706.07913v1","created_at":"2026-05-18T00:41:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.07913","created_at":"2026-05-18T00:41:47Z"},{"alias_kind":"pith_short_12","alias_value":"XP7EGWRUKJXC","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"XP7EGWRUKJXCIXWK","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"XP7EGWRU","created_at":"2026-05-18T12:31:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:XP7EGWRUKJXCIXWK3TGQYB242I","target":"record","payload":{"canonical_record":{"source":{"id":"1706.07913","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-24T06:08:27Z","cross_cats_sorted":["cs.CL","cs.IR"],"title_canon_sha256":"91de8ceed584c316b3f0f81affc5abda29980fd7e975f9ec592da46997c89a36","abstract_canon_sha256":"32cd264c7bed9b162b42555b7aea9deb242b11e6bc27ec194cca2c968bdfe6aa"},"schema_version":"1.0"},"canonical_sha256":"bbfe435a34526e245ecadccd0c075cd20793d8dca54f021fb7476c79e59a18cb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:41:47.148432Z","signature_b64":"CZs9u3h2xBWclYUKnh3iFSy8Ire8JywIjj2/OcTU7Fl1lnXRRqp5K5zqCbveKXDukXlUZO1l3fXIsoRv5jqeDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bbfe435a34526e245ecadccd0c075cd20793d8dca54f021fb7476c79e59a18cb","last_reissued_at":"2026-05-18T00:41:47.147932Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:41:47.147932Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1706.07913","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":"2026-05-18T00:41:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SbNeGDudRqoAs9r+71KKpnHvqhHmxqXfFUW4Zd0bjbN8A4JzCPSIpD9j2LgrN4f8pkJ6UURJa6loutK2ZksPAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T13:53:22.657553Z"},"content_sha256":"c8b5e541d851b56459218e6a0e0f004675f9820f323ad2d2951e8dbd41af1042","schema_version":"1.0","event_id":"sha256:c8b5e541d851b56459218e6a0e0f004675f9820f323ad2d2951e8dbd41af1042"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:XP7EGWRUKJXCIXWK3TGQYB242I","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Semi-supervised Text Categorization Using Recursive K-means Clustering","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.IR"],"primary_cat":"cs.LG","authors_text":"D.S. Guru, Harsha S. Gowda, Lavanya Narayana Raju, Mahamad Suhil","submitted_at":"2017-06-24T06:08:27Z","abstract_excerpt":"In this paper, we present a semi-supervised learning algorithm for classification of text documents. A method of labeling unlabeled text documents is presented. The presented method is based on the principle of divide and conquer strategy. It uses recursive K-means algorithm for partitioning both labeled and unlabeled data collection. The K-means algorithm is applied recursively on each partition till a desired level partition is achieved such that each partition contains labeled documents of a single class. Once the desired clusters are obtained, the respective cluster centroids are considere"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.07913","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":"2026-05-18T00:41:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"itPMRburiUdRZguq6YFK2br5xBocHUYm7XfJOV5MQ2Lr5UZS2aynug6QFt41ijqqeReskvNpTPWO3yG95F5sDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T13:53:22.657889Z"},"content_sha256":"1628aa1660dee8a3ed33371519debba8484abf1a84d7e52112f6000e03f92805","schema_version":"1.0","event_id":"sha256:1628aa1660dee8a3ed33371519debba8484abf1a84d7e52112f6000e03f92805"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XP7EGWRUKJXCIXWK3TGQYB242I/bundle.json","state_url":"https://pith.science/pith/XP7EGWRUKJXCIXWK3TGQYB242I/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XP7EGWRUKJXCIXWK3TGQYB242I/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":"2026-05-28T13:53:22Z","links":{"resolver":"https://pith.science/pith/XP7EGWRUKJXCIXWK3TGQYB242I","bundle":"https://pith.science/pith/XP7EGWRUKJXCIXWK3TGQYB242I/bundle.json","state":"https://pith.science/pith/XP7EGWRUKJXCIXWK3TGQYB242I/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XP7EGWRUKJXCIXWK3TGQYB242I/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:XP7EGWRUKJXCIXWK3TGQYB242I","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":"32cd264c7bed9b162b42555b7aea9deb242b11e6bc27ec194cca2c968bdfe6aa","cross_cats_sorted":["cs.CL","cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-24T06:08:27Z","title_canon_sha256":"91de8ceed584c316b3f0f81affc5abda29980fd7e975f9ec592da46997c89a36"},"schema_version":"1.0","source":{"id":"1706.07913","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1706.07913","created_at":"2026-05-18T00:41:47Z"},{"alias_kind":"arxiv_version","alias_value":"1706.07913v1","created_at":"2026-05-18T00:41:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.07913","created_at":"2026-05-18T00:41:47Z"},{"alias_kind":"pith_short_12","alias_value":"XP7EGWRUKJXC","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"XP7EGWRUKJXCIXWK","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"XP7EGWRU","created_at":"2026-05-18T12:31:56Z"}],"graph_snapshots":[{"event_id":"sha256:1628aa1660dee8a3ed33371519debba8484abf1a84d7e52112f6000e03f92805","target":"graph","created_at":"2026-05-18T00:41:47Z","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":"In this paper, we present a semi-supervised learning algorithm for classification of text documents. A method of labeling unlabeled text documents is presented. The presented method is based on the principle of divide and conquer strategy. It uses recursive K-means algorithm for partitioning both labeled and unlabeled data collection. The K-means algorithm is applied recursively on each partition till a desired level partition is achieved such that each partition contains labeled documents of a single class. Once the desired clusters are obtained, the respective cluster centroids are considere","authors_text":"D.S. Guru, Harsha S. Gowda, Lavanya Narayana Raju, Mahamad Suhil","cross_cats":["cs.CL","cs.IR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-24T06:08:27Z","title":"Semi-supervised Text Categorization Using Recursive K-means Clustering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.07913","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:c8b5e541d851b56459218e6a0e0f004675f9820f323ad2d2951e8dbd41af1042","target":"record","created_at":"2026-05-18T00:41:47Z","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":"32cd264c7bed9b162b42555b7aea9deb242b11e6bc27ec194cca2c968bdfe6aa","cross_cats_sorted":["cs.CL","cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-24T06:08:27Z","title_canon_sha256":"91de8ceed584c316b3f0f81affc5abda29980fd7e975f9ec592da46997c89a36"},"schema_version":"1.0","source":{"id":"1706.07913","kind":"arxiv","version":1}},"canonical_sha256":"bbfe435a34526e245ecadccd0c075cd20793d8dca54f021fb7476c79e59a18cb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bbfe435a34526e245ecadccd0c075cd20793d8dca54f021fb7476c79e59a18cb","first_computed_at":"2026-05-18T00:41:47.147932Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:41:47.147932Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CZs9u3h2xBWclYUKnh3iFSy8Ire8JywIjj2/OcTU7Fl1lnXRRqp5K5zqCbveKXDukXlUZO1l3fXIsoRv5jqeDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:41:47.148432Z","signed_message":"canonical_sha256_bytes"},"source_id":"1706.07913","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c8b5e541d851b56459218e6a0e0f004675f9820f323ad2d2951e8dbd41af1042","sha256:1628aa1660dee8a3ed33371519debba8484abf1a84d7e52112f6000e03f92805"],"state_sha256":"d95a7abaafbf51494d8e08ab8083f0db8f111086fadc8a171731798e1ef53b96"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DUgxiwwgiLPAxEPqgTh53BapoDrusUOoSZh96RUEzCU8322aZzkGyQjP7gnu/223oyYWpiBm4mHZPFZmFxjQBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T13:53:22.659776Z","bundle_sha256":"59efc8028f9c84859749a45e0fec66947ee41c94ee7cedae00ccb54ba71a627f"}}