{"id":"https://openalex.org/W4417530021","doi":"https://doi.org/10.48550/arxiv.2512.16255","title":"Multi-granularity Spatiotemporal Flow Patterns","display_name":"Multi-granularity Spatiotemporal Flow Patterns","publication_year":2025,"publication_date":"2025-12-18","ids":{"openalex":"https://openalex.org/W4417530021","doi":"https://doi.org/10.48550/arxiv.2512.16255"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2512.16255","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.16255","pdf_url":"https://arxiv.org/pdf/2512.16255","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2512.16255","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080325696","display_name":"Chrysanthi Kosyfaki","orcid":"https://orcid.org/0000-0002-0920-1437"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kosyfaki, Chrysanthi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045731304","display_name":"Nikos Mamoulis","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mamoulis, Nikos","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005847882","display_name":"Reynold Cheng","orcid":"https://orcid.org/0000-0002-9480-9809"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Reynold","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5120869809","display_name":"Ben Kai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kao, Ben","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5080325696"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.7213000059127808,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.7213000059127808,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.18140000104904175,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.019099999219179153,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.641700029373169},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.5539000034332275},{"id":"https://openalex.org/keywords/travel-time","display_name":"Travel time","score":0.3953000009059906},{"id":"https://openalex.org/keywords/pattern-detection","display_name":"Pattern detection","score":0.38920000195503235},{"id":"https://openalex.org/keywords/flow-map","display_name":"Flow map","score":0.3736000061035156},{"id":"https://openalex.org/keywords/movement","display_name":"Movement (music)","score":0.31220000982284546},{"id":"https://openalex.org/keywords/pattern-analysis","display_name":"Pattern analysis","score":0.28700000047683716}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7109000086784363},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.641700029373169},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.5539000034332275},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4731999933719635},{"id":"https://openalex.org/C2985733770","wikidata":"https://www.wikidata.org/wiki/Q1233007","display_name":"Travel time","level":2,"score":0.3953000009059906},{"id":"https://openalex.org/C2776088427","wikidata":"https://www.wikidata.org/wiki/Q378859","display_name":"Pattern detection","level":2,"score":0.38920000195503235},{"id":"https://openalex.org/C25902001","wikidata":"https://www.wikidata.org/wiki/Q1024820","display_name":"Flow map","level":3,"score":0.3736000061035156},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32280001044273376},{"id":"https://openalex.org/C2780226923","wikidata":"https://www.wikidata.org/wiki/Q929848","display_name":"Movement (music)","level":2,"score":0.31220000982284546},{"id":"https://openalex.org/C2985264313","wikidata":"https://www.wikidata.org/wiki/Q378859","display_name":"Pattern analysis","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C3018263672","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Efficient algorithm","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2800999879837036},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C2988382989","wikidata":"https://www.wikidata.org/wiki/Q370685","display_name":"Data space","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C130187892","wikidata":"https://www.wikidata.org/wiki/Q133327","display_name":"Spacetime","level":2,"score":0.26919999718666077},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.26750001311302185}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2512.16255","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.16255","pdf_url":"https://arxiv.org/pdf/2512.16255","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2512.16255","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.16255","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2512.16255","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.16255","pdf_url":"https://arxiv.org/pdf/2512.16255","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Analyzing":[0],"flow":[1,152],"of":[2,9,48,96,128,141],"objects":[3],"or":[4,17],"data":[5,27],"at":[6,57],"different":[7,58,114],"granularities":[8],"space":[10,91],"and":[11,66,73,83,92,106,139,148],"time":[12],"can":[13,37],"unveil":[14],"interesting":[15,150],"insights":[16],"trends.":[18],"For":[19],"example,":[20],"transportation":[21],"companies,":[22],"by":[23],"aggregating":[24],"passenger":[25,53],"travel":[26],"(e.g.,":[28],"counting":[29],"passengers":[30],"traveling":[31],"from":[32],"one":[33],"region":[34],"to":[35,113],"another),":[36],"analyze":[38],"movement":[39],"behavior.":[40],"In":[41],"this":[42],"paper,":[43],"we":[44,118],"study":[45],"the":[46,89,93,137],"problem":[47],"finding":[49],"important":[50],"trends":[51],"in":[52,154],"movements":[54],"between":[55],"regions":[56],"granularities.":[59],"We":[60,81,99,135],"define":[61],"Origin":[62],"(O),":[63],"Destination":[64],"(D),":[65],"Time":[67],"(T":[68],")":[69],"patterns":[70,105,127,153],"(ODT":[71],"patterns)":[72,108],"propose":[74,101,119],"a":[75,132],"bottom-up":[76],"algorithm":[77],"that":[78,86,109,123],"enumerates":[79],"them.":[80,155],"suggest":[82],"employ":[84],"optimizations":[85],"greatly":[87],"reduce":[88],"search":[90],"computational":[94],"cost":[95],"pattern":[97,102],"enumeration.":[98],"also":[100],"variants":[103],"(constrained":[104],"top-k":[107],"could":[110],"be":[111],"useful":[112],"applications":[115],"scenarios.":[116],"Finally,":[117],"an":[120],"approximate":[121],"solution":[122],"fast":[124],"identifies":[125],"ODT":[126,151],"specific":[129],"sizes,":[130],"following":[131],"generate-and-test":[133],"approach.":[134],"evaluate":[136],"efficiency":[138],"effectiveness":[140],"our":[142],"methods":[143],"on":[144],"three":[145],"real":[146],"datasets":[147],"showcase":[149]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-12-21T00:00:00"}