{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:U5CV6IJ2PAHCRQAGZMKZ3MBSYW","short_pith_number":"pith:U5CV6IJ2","canonical_record":{"source":{"id":"1403.3460","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2014-03-13T23:22:21Z","cross_cats_sorted":["cs.CL","cs.DB","cs.IR"],"title_canon_sha256":"4207e84a338eefb5894c7a6cfaf8a09aad29428b7b46c5f32cc82ee330fc08a2","abstract_canon_sha256":"40295faefa24efb78d34344a1ab42b3546cfeb45e5ad69f0d4527bda1f4eae01"},"schema_version":"1.0"},"canonical_sha256":"a7455f213a780e28c006cb159db032c5ab5d8d41f858c049826617b2d0d16e17","source":{"kind":"arxiv","id":"1403.3460","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1403.3460","created_at":"2026-05-18T02:56:20Z"},{"alias_kind":"arxiv_version","alias_value":"1403.3460v1","created_at":"2026-05-18T02:56:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1403.3460","created_at":"2026-05-18T02:56:20Z"},{"alias_kind":"pith_short_12","alias_value":"U5CV6IJ2PAHC","created_at":"2026-05-18T12:28:52Z"},{"alias_kind":"pith_short_16","alias_value":"U5CV6IJ2PAHCRQAG","created_at":"2026-05-18T12:28:52Z"},{"alias_kind":"pith_short_8","alias_value":"U5CV6IJ2","created_at":"2026-05-18T12:28:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:U5CV6IJ2PAHCRQAGZMKZ3MBSYW","target":"record","payload":{"canonical_record":{"source":{"id":"1403.3460","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2014-03-13T23:22:21Z","cross_cats_sorted":["cs.CL","cs.DB","cs.IR"],"title_canon_sha256":"4207e84a338eefb5894c7a6cfaf8a09aad29428b7b46c5f32cc82ee330fc08a2","abstract_canon_sha256":"40295faefa24efb78d34344a1ab42b3546cfeb45e5ad69f0d4527bda1f4eae01"},"schema_version":"1.0"},"canonical_sha256":"a7455f213a780e28c006cb159db032c5ab5d8d41f858c049826617b2d0d16e17","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:56:20.367751Z","signature_b64":"Foc9K2QV1upRmUO7rUY3ChaKd4BKDrQq8JCl1jja3hcMDijCb7QDDv4Vs070OfDZTYxzwiFQD+ueVb0AMlNzDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a7455f213a780e28c006cb159db032c5ab5d8d41f858c049826617b2d0d16e17","last_reissued_at":"2026-05-18T02:56:20.367022Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:56:20.367022Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1403.3460","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":"2026-05-18T02:56:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AqpHICbfacs3YpYHKSOzkG2oibiPS8NM/7Kv0dBZfKx29JtpCr76psm7qbg+lZ1agKOKuS5ZgxMZLbok1HXODw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T19:13:13.647637Z"},"content_sha256":"7513c3102ccec7e435d8d37817092b36e8028ac99403f6eb68a9730ce9a693bb","schema_version":"1.0","event_id":"sha256:7513c3102ccec7e435d8d37817092b36e8028ac99403f6eb68a9730ce9a693bb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:U5CV6IJ2PAHCRQAGZMKZ3MBSYW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Scalable and Robust Construction of Topical Hierarchies","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.DB","cs.IR"],"primary_cat":"cs.LG","authors_text":"Chi Wang, Jiawei Han, Xueqing Liu, Yanglei Song","submitted_at":"2014-03-13T23:22:21Z","abstract_excerpt":"Automated generation of high-quality topical hierarchies for a text collection is a dream problem in knowledge engineering with many valuable applications. In this paper a scalable and robust algorithm is proposed for constructing a hierarchy of topics from a text collection. We divide and conquer the problem using a top-down recursive framework, based on a tensor orthogonal decomposition technique. We solve a critical challenge to perform scalable inference for our newly designed hierarchical topic model. Experiments with various real-world datasets illustrate its ability to generate robust, "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1403.3460","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":"2026-05-18T02:56:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gXKbXhgQ7pEBmGwA/ZpKY5M1AN1wTe3P872mSOe2lDIsBQaInrqDiX8XCKn4moDmz5gw4s3NPoz97RFQg/PQAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T19:13:13.648346Z"},"content_sha256":"ef37294c3be3c15c830c7c0897686cea3cc875075149e6c9affb26f0371190c5","schema_version":"1.0","event_id":"sha256:ef37294c3be3c15c830c7c0897686cea3cc875075149e6c9affb26f0371190c5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/U5CV6IJ2PAHCRQAGZMKZ3MBSYW/bundle.json","state_url":"https://pith.science/pith/U5CV6IJ2PAHCRQAGZMKZ3MBSYW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/U5CV6IJ2PAHCRQAGZMKZ3MBSYW/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":"2026-06-08T19:13:13Z","links":{"resolver":"https://pith.science/pith/U5CV6IJ2PAHCRQAGZMKZ3MBSYW","bundle":"https://pith.science/pith/U5CV6IJ2PAHCRQAGZMKZ3MBSYW/bundle.json","state":"https://pith.science/pith/U5CV6IJ2PAHCRQAGZMKZ3MBSYW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/U5CV6IJ2PAHCRQAGZMKZ3MBSYW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:U5CV6IJ2PAHCRQAGZMKZ3MBSYW","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":"40295faefa24efb78d34344a1ab42b3546cfeb45e5ad69f0d4527bda1f4eae01","cross_cats_sorted":["cs.CL","cs.DB","cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2014-03-13T23:22:21Z","title_canon_sha256":"4207e84a338eefb5894c7a6cfaf8a09aad29428b7b46c5f32cc82ee330fc08a2"},"schema_version":"1.0","source":{"id":"1403.3460","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1403.3460","created_at":"2026-05-18T02:56:20Z"},{"alias_kind":"arxiv_version","alias_value":"1403.3460v1","created_at":"2026-05-18T02:56:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1403.3460","created_at":"2026-05-18T02:56:20Z"},{"alias_kind":"pith_short_12","alias_value":"U5CV6IJ2PAHC","created_at":"2026-05-18T12:28:52Z"},{"alias_kind":"pith_short_16","alias_value":"U5CV6IJ2PAHCRQAG","created_at":"2026-05-18T12:28:52Z"},{"alias_kind":"pith_short_8","alias_value":"U5CV6IJ2","created_at":"2026-05-18T12:28:52Z"}],"graph_snapshots":[{"event_id":"sha256:ef37294c3be3c15c830c7c0897686cea3cc875075149e6c9affb26f0371190c5","target":"graph","created_at":"2026-05-18T02:56:20Z","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":"Automated generation of high-quality topical hierarchies for a text collection is a dream problem in knowledge engineering with many valuable applications. In this paper a scalable and robust algorithm is proposed for constructing a hierarchy of topics from a text collection. We divide and conquer the problem using a top-down recursive framework, based on a tensor orthogonal decomposition technique. We solve a critical challenge to perform scalable inference for our newly designed hierarchical topic model. Experiments with various real-world datasets illustrate its ability to generate robust, ","authors_text":"Chi Wang, Jiawei Han, Xueqing Liu, Yanglei Song","cross_cats":["cs.CL","cs.DB","cs.IR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2014-03-13T23:22:21Z","title":"Scalable and Robust Construction of Topical Hierarchies"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1403.3460","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":"sha256:7513c3102ccec7e435d8d37817092b36e8028ac99403f6eb68a9730ce9a693bb","target":"record","created_at":"2026-05-18T02:56:20Z","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":"40295faefa24efb78d34344a1ab42b3546cfeb45e5ad69f0d4527bda1f4eae01","cross_cats_sorted":["cs.CL","cs.DB","cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2014-03-13T23:22:21Z","title_canon_sha256":"4207e84a338eefb5894c7a6cfaf8a09aad29428b7b46c5f32cc82ee330fc08a2"},"schema_version":"1.0","source":{"id":"1403.3460","kind":"arxiv","version":1}},"canonical_sha256":"a7455f213a780e28c006cb159db032c5ab5d8d41f858c049826617b2d0d16e17","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a7455f213a780e28c006cb159db032c5ab5d8d41f858c049826617b2d0d16e17","first_computed_at":"2026-05-18T02:56:20.367022Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:56:20.367022Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Foc9K2QV1upRmUO7rUY3ChaKd4BKDrQq8JCl1jja3hcMDijCb7QDDv4Vs070OfDZTYxzwiFQD+ueVb0AMlNzDw==","signature_status":"signed_v1","signed_at":"2026-05-18T02:56:20.367751Z","signed_message":"canonical_sha256_bytes"},"source_id":"1403.3460","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7513c3102ccec7e435d8d37817092b36e8028ac99403f6eb68a9730ce9a693bb","sha256:ef37294c3be3c15c830c7c0897686cea3cc875075149e6c9affb26f0371190c5"],"state_sha256":"c9fb575ad9e508f97c3813a61607c97fe52ac79438ad05781a75cf4432b536bf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JrH3pXrJCtuOoHtNfcQDpjdXzLNV14GCnGOBSUmQJGttvsgNkTjdDtkk+TRPPVjPpk7Vu6QEK+XuSZriaroMCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-08T19:13:13.652446Z","bundle_sha256":"11bbfd45f11f29833bdf74cb059b2b02c0c0edfe1a4df1dbbbf81667bcbe10d4"}}