{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:SKUZOBWPFPLEDBKRW5RQ3A4IWP","short_pith_number":"pith:SKUZOBWP","schema_version":"1.0","canonical_sha256":"92a99706cf2bd6418551b7630d8388b3e6bb76d5c190ee7206428cbf54b6f571","source":{"kind":"arxiv","id":"2012.11796","version":1},"attestation_state":"computed","paper":{"title":"Multiple-Perspective Clustering of Passive Wi-Fi Sensing Trajectory Data","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"cs.LG","authors_text":"Bige Tuncer, Billy Pik Lik Lau, Chau Yuen, Keng Hua Chong, Yuren Zhou, Zann Koh","submitted_at":"2020-12-22T02:30:16Z","abstract_excerpt":"Information about the spatiotemporal flow of humans within an urban context has a wide plethora of applications. Currently, although there are many different approaches to collect such data, there lacks a standardized framework to analyze it. The focus of this paper is on the analysis of the data collected through passive Wi-Fi sensing, as such passively collected data can have a wide coverage at low cost. We propose a systematic approach by using unsupervised machine learning methods, namely k-means clustering and hierarchical agglomerative clustering (HAC) to analyze data collected through s"},"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":"2012.11796","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2020-12-22T02:30:16Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"06adc2447a637737cd5d9215f44f8344ca856227bb48cb7cb0362f73300faf4a","abstract_canon_sha256":"e7ee2c2feccd45bde99b02da0d52fc83a6ea1b8a009fdec9163c1705a3001047"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:01:21.233710Z","signature_b64":"CPe5MuGszI0zColX540lrkFoGoP15118vzweKyuKjDea9eSIvGOTRoHyY9nwJWEm7FxRXT0BLWKv6uxE7JdJBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"92a99706cf2bd6418551b7630d8388b3e6bb76d5c190ee7206428cbf54b6f571","last_reissued_at":"2026-07-05T02:01:21.233375Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:01:21.233375Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Multiple-Perspective Clustering of Passive Wi-Fi Sensing Trajectory Data","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"cs.LG","authors_text":"Bige Tuncer, Billy Pik Lik Lau, Chau Yuen, Keng Hua Chong, Yuren Zhou, Zann Koh","submitted_at":"2020-12-22T02:30:16Z","abstract_excerpt":"Information about the spatiotemporal flow of humans within an urban context has a wide plethora of applications. Currently, although there are many different approaches to collect such data, there lacks a standardized framework to analyze it. The focus of this paper is on the analysis of the data collected through passive Wi-Fi sensing, as such passively collected data can have a wide coverage at low cost. We propose a systematic approach by using unsupervised machine learning methods, namely k-means clustering and hierarchical agglomerative clustering (HAC) to analyze data collected through s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.11796","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2012.11796/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":"2012.11796","created_at":"2026-07-05T02:01:21.233432+00:00"},{"alias_kind":"arxiv_version","alias_value":"2012.11796v1","created_at":"2026-07-05T02:01:21.233432+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.11796","created_at":"2026-07-05T02:01:21.233432+00:00"},{"alias_kind":"pith_short_12","alias_value":"SKUZOBWPFPLE","created_at":"2026-07-05T02:01:21.233432+00:00"},{"alias_kind":"pith_short_16","alias_value":"SKUZOBWPFPLEDBKR","created_at":"2026-07-05T02:01:21.233432+00:00"},{"alias_kind":"pith_short_8","alias_value":"SKUZOBWP","created_at":"2026-07-05T02:01:21.233432+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/SKUZOBWPFPLEDBKRW5RQ3A4IWP","json":"https://pith.science/pith/SKUZOBWPFPLEDBKRW5RQ3A4IWP.json","graph_json":"https://pith.science/api/pith-number/SKUZOBWPFPLEDBKRW5RQ3A4IWP/graph.json","events_json":"https://pith.science/api/pith-number/SKUZOBWPFPLEDBKRW5RQ3A4IWP/events.json","paper":"https://pith.science/paper/SKUZOBWP"},"agent_actions":{"view_html":"https://pith.science/pith/SKUZOBWPFPLEDBKRW5RQ3A4IWP","download_json":"https://pith.science/pith/SKUZOBWPFPLEDBKRW5RQ3A4IWP.json","view_paper":"https://pith.science/paper/SKUZOBWP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2012.11796&json=true","fetch_graph":"https://pith.science/api/pith-number/SKUZOBWPFPLEDBKRW5RQ3A4IWP/graph.json","fetch_events":"https://pith.science/api/pith-number/SKUZOBWPFPLEDBKRW5RQ3A4IWP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SKUZOBWPFPLEDBKRW5RQ3A4IWP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SKUZOBWPFPLEDBKRW5RQ3A4IWP/action/storage_attestation","attest_author":"https://pith.science/pith/SKUZOBWPFPLEDBKRW5RQ3A4IWP/action/author_attestation","sign_citation":"https://pith.science/pith/SKUZOBWPFPLEDBKRW5RQ3A4IWP/action/citation_signature","submit_replication":"https://pith.science/pith/SKUZOBWPFPLEDBKRW5RQ3A4IWP/action/replication_record"}},"created_at":"2026-07-05T02:01:21.233432+00:00","updated_at":"2026-07-05T02:01:21.233432+00:00"}