{"id":"https://openalex.org/W7161846068","doi":"https://doi.org/10.48550/arxiv.2605.18777","title":"XFlowMap: Cross-Scale Generalization and Mapping of Massive Origin-Destination Data","display_name":"XFlowMap: Cross-Scale Generalization and Mapping of Massive Origin-Destination Data","publication_year":2026,"publication_date":"2026-04-23","ids":{"openalex":"https://openalex.org/W7161846068","doi":"https://doi.org/10.48550/arxiv.2605.18777"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.18777","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.18777","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.18777","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003854328","display_name":"Diansheng Guo","orcid":"https://orcid.org/0000-0003-3483-4153"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Diansheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136549873","display_name":"Hai Jin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Hai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.4763999879360199,"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"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.4763999879360199,"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/T11106","display_name":"Data Management and Algorithms","score":0.3337000012397766,"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/T10757","display_name":"Geographic Information Systems Studies","score":0.07930000126361847,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.6534000039100647},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6079000234603882},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.60589998960495},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.5942999720573425},{"id":"https://openalex.org/keywords/flow-map","display_name":"Flow map","score":0.5842999815940857},{"id":"https://openalex.org/keywords/cartographic-generalization","display_name":"Cartographic generalization","score":0.49399998784065247},{"id":"https://openalex.org/keywords/data-exploration","display_name":"Data exploration","score":0.38269999623298645},{"id":"https://openalex.org/keywords/interpretation","display_name":"Interpretation (philosophy)","score":0.37560001015663147}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7053999900817871},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.6534000039100647},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6079000234603882},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.60589998960495},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5942999720573425},{"id":"https://openalex.org/C25902001","wikidata":"https://www.wikidata.org/wiki/Q1024820","display_name":"Flow map","level":3,"score":0.5842999815940857},{"id":"https://openalex.org/C196031653","wikidata":"https://www.wikidata.org/wiki/Q1501867","display_name":"Cartographic generalization","level":3,"score":0.49399998784065247},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48829999566078186},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4311000108718872},{"id":"https://openalex.org/C2780977526","wikidata":"https://www.wikidata.org/wiki/Q42417149","display_name":"Data exploration","level":3,"score":0.38269999623298645},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.37560001015663147},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.32919999957084656},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3280999958515167},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3221000134944916},{"id":"https://openalex.org/C134400042","wikidata":"https://www.wikidata.org/wiki/Q2372244","display_name":"Symbol (formal)","level":2,"score":0.3034999966621399},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3025999963283539},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.2881999909877777},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.288100004196167},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C489000","wikidata":"https://www.wikidata.org/wiki/Q747385","display_name":"Data flow diagram","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.2597000002861023}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.18777","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.18777","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.18777","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.18777","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7239217162132263}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Mapping":[0],"large":[1,190],"origin-destination":[2,71,103],"(OD)":[3],"datasets":[4],"remains":[5],"challenging":[6],"because":[7],"flow":[8,53,58,72,78,94,104,116,127,163,181,187],"maps":[9,188],"become":[10],"cluttered,":[11],"meaningful":[12,179],"patterns":[13,79,182],"occur":[14],"at":[15,80],"multiple":[16],"spatial":[17],"scales,":[18,86],"and":[19,42,61,68,84,90,113,134,146,154,157,169,183,197],"existing":[20],"flow-mapping":[21],"approaches":[22],"frequently":[23],"rely":[24],"on":[25],"predefined":[26],"aggregation":[27],"units":[28],"or":[29],"manual":[30],"generalization.":[31],"This":[32],"paper":[33],"presents":[34],"XFlowMap,":[35],"a":[36,62,92,125,138],"framework":[37,50,142],"for":[38,66,189],"the":[39,49,175],"cross-scale":[40,52,115,180],"generalization":[41],"mapping":[43,160],"of":[44,101,161],"massive":[45],"OD":[46,135,148],"data.":[47,164],"Specifically,":[48],"integrates":[51,130],"pattern":[54],"(cluster)":[55],"detection,":[56],"automated":[57],"map":[59,95],"generalization,":[60],"new":[63,93],"cartographic":[64],"representation":[65,96],"analyzing":[67],"visualizing":[69],"complex":[70,102],"structures.":[73],"The":[74,118,141],"approach":[75],"detects":[76],"salient":[77],"their":[81],"appropriate":[82],"origin":[83],"destination":[85],"extracts":[87,178],"high-level":[88],"structures,":[89],"generates":[91],"that":[97,129,174],"supports":[98,143],"holistic":[99],"interpretation":[100],"patterns.":[105],"A":[106],"scan-statistic-based":[107],"procedure":[108],"is":[109,150],"developed":[110],"to":[111,152],"evaluate":[112],"generalize":[114],"clusters.":[117],"detected":[119],"clusters":[120],"are":[121],"then":[122],"visualized":[123],"using":[124],"novel":[126],"symbol":[128],"location,":[131],"direction,":[132],"strength,":[133],"scales":[136],"in":[137],"single":[139],"representation.":[140],"both":[144,194],"area-based":[145],"point-based":[147],"data,":[149],"robust":[151],"sparse":[153],"noisy":[155],"datasets,":[156,192],"enables":[158],"comparative":[159],"stratified":[162],"Experiments":[165],"with":[166],"synthetic":[167],"data":[168,172],"U.S.":[170],"migration":[171],"demonstrate":[173],"method":[176],"effectively":[177],"produces":[184],"clear,":[185],"information-rich":[186],"mobility":[191],"supporting":[193],"static":[195],"presentation":[196],"interactive":[198],"exploration.":[199]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-21T00:00:00"}