{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:R7SUGJJDB2NEDU7PPOTIMDWTMZ","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":"d80df4705c1312a8fc7447aa518d568a9a2289611dc29491d1c6c9323677a617","cross_cats_sorted":["cs.IR","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-10-07T08:18:12Z","title_canon_sha256":"c33ae2d7401af3335e156b5de98ecfe8d00cb905268d7454fea03d2577b9a29f"},"schema_version":"1.0","source":{"id":"1710.02650","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.02650","created_at":"2026-05-18T00:24:30Z"},{"alias_kind":"arxiv_version","alias_value":"1710.02650v2","created_at":"2026-05-18T00:24:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.02650","created_at":"2026-05-18T00:24:30Z"},{"alias_kind":"pith_short_12","alias_value":"R7SUGJJDB2NE","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_16","alias_value":"R7SUGJJDB2NEDU7P","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_8","alias_value":"R7SUGJJD","created_at":"2026-05-18T12:31:39Z"}],"graph_snapshots":[{"event_id":"sha256:27864aa0d2ab58b8ddb9f288bc15a07a023c759f094acc3b691da388af5ce1d7","target":"graph","created_at":"2026-05-18T00:24:30Z","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":"Current topic models often suffer from discovering topics not matching human intuition, unnatural switching of topics within documents and high computational demands. We address these concerns by proposing a topic model and an inference algorithm based on automatically identifying characteristic keywords for topics. Keywords influence topic-assignments of nearby words. Our algorithm learns (key)word-topic scores and it self-regulates the number of topics. Inference is simple and easily parallelizable. Qualitative analysis yields comparable results to state-of-the-art models (eg. LDA), but with","authors_text":"Johannes Schneider","cross_cats":["cs.IR","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-10-07T08:18:12Z","title":"Topic Modeling based on Keywords and Context"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.02650","kind":"arxiv","version":2},"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":"sha256:2bfadec1d2dd1a2a92ef9c79272855534d19f7c3cc23f1affffccabbb20e42e1","target":"record","created_at":"2026-05-18T00:24:30Z","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":"d80df4705c1312a8fc7447aa518d568a9a2289611dc29491d1c6c9323677a617","cross_cats_sorted":["cs.IR","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-10-07T08:18:12Z","title_canon_sha256":"c33ae2d7401af3335e156b5de98ecfe8d00cb905268d7454fea03d2577b9a29f"},"schema_version":"1.0","source":{"id":"1710.02650","kind":"arxiv","version":2}},"canonical_sha256":"8fe54325230e9a41d3ef7ba6860ed3664de793cbb7ff484727fa82df2e993865","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8fe54325230e9a41d3ef7ba6860ed3664de793cbb7ff484727fa82df2e993865","first_computed_at":"2026-05-18T00:24:30.623962Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:24:30.623962Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"h6obYX8AJf2Z42cw6ypOvmkZGlIMne8aESv7nRQIDrXgrkgFIRZSvA6+lur+T9gLkzHNROEcBwGiZ8A594n9CA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:24:30.624434Z","signed_message":"canonical_sha256_bytes"},"source_id":"1710.02650","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2bfadec1d2dd1a2a92ef9c79272855534d19f7c3cc23f1affffccabbb20e42e1","sha256:27864aa0d2ab58b8ddb9f288bc15a07a023c759f094acc3b691da388af5ce1d7"],"state_sha256":"2051515b6ea15c1d43db67e2e3d46352b5c48442c51a3030d24abaa4641b481d"}