{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:XEWAC4GECGHANMHYMMD54RQIYO","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":"788cd3ebe1137265ad320e8d232ce291b257646c2278ca27415caa099b2e0c51","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-11-13T17:53:23Z","title_canon_sha256":"9f1efc1b1b5898d10bbeb49873ea04da5d7e22d0d3d41c1b17c1df852c4f99ae"},"schema_version":"1.0","source":{"id":"2411.08814","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.08814","created_at":"2026-07-05T09:35:02Z"},{"alias_kind":"arxiv_version","alias_value":"2411.08814v1","created_at":"2026-07-05T09:35:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.08814","created_at":"2026-07-05T09:35:02Z"},{"alias_kind":"pith_short_12","alias_value":"XEWAC4GECGHA","created_at":"2026-07-05T09:35:02Z"},{"alias_kind":"pith_short_16","alias_value":"XEWAC4GECGHANMHY","created_at":"2026-07-05T09:35:02Z"},{"alias_kind":"pith_short_8","alias_value":"XEWAC4GE","created_at":"2026-07-05T09:35:02Z"}],"graph_snapshots":[{"event_id":"sha256:385a741cbd513218397a9383c7449f52e3f9d1f9cd22dce471ed3dbb44a1f08f","target":"graph","created_at":"2026-07-05T09:35:02Z","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/2411.08814/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Humans naturally follow distinct patterns when conducting their daily activities, which are driven by established practices and processes, such as production workflows, social norms and daily routines. Human activity recognition (HAR) algorithms usually use neural networks or machine learning techniques to analyse inherent relationships within the data. However, these approaches often overlook the contextual information in which the data are generated, potentially limiting their effectiveness. We propose a novel approach that incorporates process information from context to enhance the HAR per","authors_text":"Jacques D. Fleuriot, Jane Hillston, Jiawei Zheng, Petros Papapanagiotou","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-11-13T17:53:23Z","title":"Process-aware Human Activity Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.08814","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":"sha256:6daaac56ddeb398f7408542f6cef2dafd4d71bc84b9025eed7cf3647acd502e7","target":"record","created_at":"2026-07-05T09:35:02Z","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":"788cd3ebe1137265ad320e8d232ce291b257646c2278ca27415caa099b2e0c51","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-11-13T17:53:23Z","title_canon_sha256":"9f1efc1b1b5898d10bbeb49873ea04da5d7e22d0d3d41c1b17c1df852c4f99ae"},"schema_version":"1.0","source":{"id":"2411.08814","kind":"arxiv","version":1}},"canonical_sha256":"b92c0170c4118e06b0f86307de4608c3a0e1164f7d575e2d4ffcef5e91784338","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b92c0170c4118e06b0f86307de4608c3a0e1164f7d575e2d4ffcef5e91784338","first_computed_at":"2026-07-05T09:35:02.900797Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:35:02.900797Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YPv0seYTA2Bit2weUkVwLLFBnSc83/wxE8uepvAmRqWqwMU08wecIhBNl64zcI/rWZ1RbE57yXtpDKMo1f8vCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:35:02.901223Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.08814","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6daaac56ddeb398f7408542f6cef2dafd4d71bc84b9025eed7cf3647acd502e7","sha256:385a741cbd513218397a9383c7449f52e3f9d1f9cd22dce471ed3dbb44a1f08f"],"state_sha256":"7199b28f316db3be537c46781c4f2caa9667667958eeb084234c707add3c99a9"}