{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:Z5O4DU34GNNQ23VVBZF3FVP7B6","short_pith_number":"pith:Z5O4DU34","schema_version":"1.0","canonical_sha256":"cf5dc1d37c335b0d6eb50e4bb2d5ff0fa7124442c5e1f705a27f55812f4d6ef5","source":{"kind":"arxiv","id":"1610.01790","version":1},"attestation_state":"computed","paper":{"title":"Predicting encounter and colocation events in metropolitan areas","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Gian Paolo Rossi, Karim Karamat Jahromi, Matteo Zignani, Sabrina Gaito","submitted_at":"2016-10-06T09:39:06Z","abstract_excerpt":"Despite an extensive literature has been devoted to mine and model mobility features, forecasting where, when and whom people will encounter/colocate still deserve further research efforts. Forecasting people's encounter and colocation features is the key point for the success of many applications ranging from epidemiology to the design of new networking paradigms and services such as delay tolerant and opportunistic networks. While many algorithms which rely on both mobility and social information have been proposed, we propose a novel encounter and colocation predictive model which predicts "},"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":"1610.01790","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2016-10-06T09:39:06Z","cross_cats_sorted":[],"title_canon_sha256":"edf67c721751f2834ff3744570ff234e0d7ae4ce8f424e493b40635d158f8b65","abstract_canon_sha256":"cf21a232f3ee426668e5a05e6fd377ec3bc9914c080c3447c837b62019b9fde2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:03:04.845437Z","signature_b64":"WHNJyadHEfXF026FcOgCuM0z67FzUtuLZF/MLzgosOY/AqHC2wfaedns6qdRS4XQYSPop6OiYEU58vGOwXYZAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cf5dc1d37c335b0d6eb50e4bb2d5ff0fa7124442c5e1f705a27f55812f4d6ef5","last_reissued_at":"2026-05-18T01:03:04.844904Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:03:04.844904Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Predicting encounter and colocation events in metropolitan areas","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Gian Paolo Rossi, Karim Karamat Jahromi, Matteo Zignani, Sabrina Gaito","submitted_at":"2016-10-06T09:39:06Z","abstract_excerpt":"Despite an extensive literature has been devoted to mine and model mobility features, forecasting where, when and whom people will encounter/colocate still deserve further research efforts. Forecasting people's encounter and colocation features is the key point for the success of many applications ranging from epidemiology to the design of new networking paradigms and services such as delay tolerant and opportunistic networks. While many algorithms which rely on both mobility and social information have been proposed, we propose a novel encounter and colocation predictive model which predicts "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1610.01790","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1610.01790","created_at":"2026-05-18T01:03:04.844988+00:00"},{"alias_kind":"arxiv_version","alias_value":"1610.01790v1","created_at":"2026-05-18T01:03:04.844988+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1610.01790","created_at":"2026-05-18T01:03:04.844988+00:00"},{"alias_kind":"pith_short_12","alias_value":"Z5O4DU34GNNQ","created_at":"2026-05-18T12:30:53.716459+00:00"},{"alias_kind":"pith_short_16","alias_value":"Z5O4DU34GNNQ23VV","created_at":"2026-05-18T12:30:53.716459+00:00"},{"alias_kind":"pith_short_8","alias_value":"Z5O4DU34","created_at":"2026-05-18T12:30:53.716459+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/Z5O4DU34GNNQ23VVBZF3FVP7B6","json":"https://pith.science/pith/Z5O4DU34GNNQ23VVBZF3FVP7B6.json","graph_json":"https://pith.science/api/pith-number/Z5O4DU34GNNQ23VVBZF3FVP7B6/graph.json","events_json":"https://pith.science/api/pith-number/Z5O4DU34GNNQ23VVBZF3FVP7B6/events.json","paper":"https://pith.science/paper/Z5O4DU34"},"agent_actions":{"view_html":"https://pith.science/pith/Z5O4DU34GNNQ23VVBZF3FVP7B6","download_json":"https://pith.science/pith/Z5O4DU34GNNQ23VVBZF3FVP7B6.json","view_paper":"https://pith.science/paper/Z5O4DU34","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1610.01790&json=true","fetch_graph":"https://pith.science/api/pith-number/Z5O4DU34GNNQ23VVBZF3FVP7B6/graph.json","fetch_events":"https://pith.science/api/pith-number/Z5O4DU34GNNQ23VVBZF3FVP7B6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/Z5O4DU34GNNQ23VVBZF3FVP7B6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/Z5O4DU34GNNQ23VVBZF3FVP7B6/action/storage_attestation","attest_author":"https://pith.science/pith/Z5O4DU34GNNQ23VVBZF3FVP7B6/action/author_attestation","sign_citation":"https://pith.science/pith/Z5O4DU34GNNQ23VVBZF3FVP7B6/action/citation_signature","submit_replication":"https://pith.science/pith/Z5O4DU34GNNQ23VVBZF3FVP7B6/action/replication_record"}},"created_at":"2026-05-18T01:03:04.844988+00:00","updated_at":"2026-05-18T01:03:04.844988+00:00"}