{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:ZXDBRWMEABMZGY7O2ZZOG3E3OJ","short_pith_number":"pith:ZXDBRWME","schema_version":"1.0","canonical_sha256":"cdc618d98400599363eed672e36c9b727780ab2b551737a37e7f71c02b29e75c","source":{"kind":"arxiv","id":"2106.08452","version":2},"attestation_state":"computed","paper":{"title":"Deep Neural Networks for Approximating Stream Reasoning with C-SPARQL","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Carolina Lopes, Jo\\~ao Leite, Ludwig Krippahl, Matthias Knorr, Ricardo Ferreira, Ricardo Gon\\c{c}alves","submitted_at":"2021-06-15T21:51:47Z","abstract_excerpt":"The amount of information produced, whether by newspapers, blogs and social networks, or by monitoring systems, is increasing rapidly. Processing all this data in real-time, while taking into consideration advanced knowledge about the problem domain, is challenging, but required in scenarios where assessing potential risks in a timely fashion is critical. C-SPARQL, a language for continuous queries over streams of RDF data, is one of the more prominent approaches in stream reasoning that provides such continuous inference capabilities over dynamic data that go beyond mere stream processing. Ho"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2106.08452","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2021-06-15T21:51:47Z","cross_cats_sorted":[],"title_canon_sha256":"15af86c250a33c7e4f575f2ebb942edd355938d56229711c25f025e1e04bdbf1","abstract_canon_sha256":"c4455a3aa0d20ff9aec8d4c9e1d4ed5a9870315b6ade9d2d7dec67a5770ae304"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:58:26.569203Z","signature_b64":"Yz6cQLUSEqykp4B3292QfYEXwIBRG2q8H20KcdtvDPR4YqFe0l8NrSlz66VQ7NelIa9VgmqoTaXI8/EXLtutAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cdc618d98400599363eed672e36c9b727780ab2b551737a37e7f71c02b29e75c","last_reissued_at":"2026-07-05T02:58:26.568849Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:58:26.568849Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Deep Neural Networks for Approximating Stream Reasoning with C-SPARQL","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Carolina Lopes, Jo\\~ao Leite, Ludwig Krippahl, Matthias Knorr, Ricardo Ferreira, Ricardo Gon\\c{c}alves","submitted_at":"2021-06-15T21:51:47Z","abstract_excerpt":"The amount of information produced, whether by newspapers, blogs and social networks, or by monitoring systems, is increasing rapidly. Processing all this data in real-time, while taking into consideration advanced knowledge about the problem domain, is challenging, but required in scenarios where assessing potential risks in a timely fashion is critical. C-SPARQL, a language for continuous queries over streams of RDF data, is one of the more prominent approaches in stream reasoning that provides such continuous inference capabilities over dynamic data that go beyond mere stream processing. Ho"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.08452","kind":"arxiv","version":2},"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/2106.08452/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2106.08452","created_at":"2026-07-05T02:58:26.568905+00:00"},{"alias_kind":"arxiv_version","alias_value":"2106.08452v2","created_at":"2026-07-05T02:58:26.568905+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.08452","created_at":"2026-07-05T02:58:26.568905+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZXDBRWMEABMZ","created_at":"2026-07-05T02:58:26.568905+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZXDBRWMEABMZGY7O","created_at":"2026-07-05T02:58:26.568905+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZXDBRWME","created_at":"2026-07-05T02:58:26.568905+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ZXDBRWMEABMZGY7O2ZZOG3E3OJ","json":"https://pith.science/pith/ZXDBRWMEABMZGY7O2ZZOG3E3OJ.json","graph_json":"https://pith.science/api/pith-number/ZXDBRWMEABMZGY7O2ZZOG3E3OJ/graph.json","events_json":"https://pith.science/api/pith-number/ZXDBRWMEABMZGY7O2ZZOG3E3OJ/events.json","paper":"https://pith.science/paper/ZXDBRWME"},"agent_actions":{"view_html":"https://pith.science/pith/ZXDBRWMEABMZGY7O2ZZOG3E3OJ","download_json":"https://pith.science/pith/ZXDBRWMEABMZGY7O2ZZOG3E3OJ.json","view_paper":"https://pith.science/paper/ZXDBRWME","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2106.08452&json=true","fetch_graph":"https://pith.science/api/pith-number/ZXDBRWMEABMZGY7O2ZZOG3E3OJ/graph.json","fetch_events":"https://pith.science/api/pith-number/ZXDBRWMEABMZGY7O2ZZOG3E3OJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZXDBRWMEABMZGY7O2ZZOG3E3OJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZXDBRWMEABMZGY7O2ZZOG3E3OJ/action/storage_attestation","attest_author":"https://pith.science/pith/ZXDBRWMEABMZGY7O2ZZOG3E3OJ/action/author_attestation","sign_citation":"https://pith.science/pith/ZXDBRWMEABMZGY7O2ZZOG3E3OJ/action/citation_signature","submit_replication":"https://pith.science/pith/ZXDBRWMEABMZGY7O2ZZOG3E3OJ/action/replication_record"}},"created_at":"2026-07-05T02:58:26.568905+00:00","updated_at":"2026-07-05T02:58:26.568905+00:00"}