{"id":"https://openalex.org/W2536648533","doi":"https://doi.org/10.1145/2983323.2983803","title":"Mining Shopping Patterns for Divergent Urban Regions by Incorporating Mobility Data","display_name":"Mining Shopping Patterns for Divergent Urban Regions by Incorporating Mobility Data","publication_year":2016,"publication_date":"2016-10-24","ids":{"openalex":"https://openalex.org/W2536648533","doi":"https://doi.org/10.1145/2983323.2983803","mag":"2536648533"},"language":"en","primary_location":{"id":"doi:10.1145/2983323.2983803","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2983323.2983803","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM International on Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014720604","display_name":"Tianran Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianran Hu","raw_affiliation_strings":["University of Rochester, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Rochester, Rochester, NY, USA","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101505570","display_name":"Ruihua Song","orcid":"https://orcid.org/0000-0001-6036-9035"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruihua Song","raw_affiliation_strings":["Microsoft Research, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100689832","display_name":"Yingzi Wang","orcid":"https://orcid.org/0000-0002-5949-3781"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingzi Wang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044651577","display_name":"Xing Xie","orcid":"https://orcid.org/0000-0002-8608-8482"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Xie","raw_affiliation_strings":["Microsoft Research, Beijng, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research, Beijng, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055469774","display_name":"Jiebo Luo","orcid":"https://orcid.org/0000-0002-4516-9729"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiebo Luo","raw_affiliation_strings":["University of Rochester, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Rochester, Rochester, NY, USA","institution_ids":["https://openalex.org/I5388228"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.5937,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.93164885,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"569","last_page":"578"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9757000207901001,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9721999764442444,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7321495413780212},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.679206132888794},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5249219536781311},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5150753855705261},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5023601055145264},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.49315541982650757},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4693520963191986},{"id":"https://openalex.org/keywords/urban-computing","display_name":"Urban computing","score":0.45949816703796387},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.41555649042129517},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3715536594390869},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3655068874359131},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3160921335220337},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.1646139919757843},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10680651664733887}],"concepts":[{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7321495413780212},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.679206132888794},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5249219536781311},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5150753855705261},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5023601055145264},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.49315541982650757},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4693520963191986},{"id":"https://openalex.org/C2778459138","wikidata":"https://www.wikidata.org/wiki/Q7900107","display_name":"Urban computing","level":2,"score":0.45949816703796387},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.41555649042129517},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3715536594390869},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3655068874359131},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3160921335220337},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.1646139919757843},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10680651664733887},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2983323.2983803","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2983323.2983803","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM International on Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7599999904632568,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W7143572","https://openalex.org/W1486638903","https://openalex.org/W1892382968","https://openalex.org/W1902027874","https://openalex.org/W1976094288","https://openalex.org/W1987228002","https://openalex.org/W1999432478","https://openalex.org/W2001488574","https://openalex.org/W2012523161","https://openalex.org/W2016535703","https://openalex.org/W2018571751","https://openalex.org/W2030214288","https://openalex.org/W2037965136","https://openalex.org/W2042281163","https://openalex.org/W2054141820","https://openalex.org/W2058560977","https://openalex.org/W2072841881","https://openalex.org/W2080678433","https://openalex.org/W2087692915","https://openalex.org/W2090641502","https://openalex.org/W2107165817","https://openalex.org/W2107357525","https://openalex.org/W2117420919","https://openalex.org/W2126895033","https://openalex.org/W2144487656","https://openalex.org/W2153207204","https://openalex.org/W2153458569","https://openalex.org/W2157205123","https://openalex.org/W2165178985","https://openalex.org/W2268305941","https://openalex.org/W2294723619","https://openalex.org/W2315106232","https://openalex.org/W2412010539","https://openalex.org/W4253336088"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703"],"abstract_inverted_index":{"What":[0],"people":[1,96,101],"buy":[2],"is":[3,52,129],"an":[4,125],"important":[5,84],"aspect":[6],"or":[7,138,198],"view":[8,85],"of":[9,60,67,86,177,192,201],"lifestyles.":[10,203],"Studying":[11],"people's":[12],"shopping":[13,49,75,161],"patterns":[14,162],"in":[15,114,167],"different":[16,168],"urban":[17,36,39,169,202],"regions":[18,70],"can":[19],"not":[20],"only":[21],"provide":[22],"valuable":[23],"information":[24,93],"for":[25,73],"various":[26],"commercial":[27],"opportunities,":[28],"but":[29],"also":[30],"enable":[31],"a":[32,53,178,196],"better":[33,197],"understanding":[34,200],"about":[35],"infrastructure":[37],"and":[38,171,194],"lifestyle.":[40],"In":[41],"this":[42,79],"paper,":[43],"we":[44,81,98,110,181],"aim":[45],"to":[46,57,104,131,184],"predict":[47],"citywide":[48],"patterns.":[50,91],"This":[51],"challenging":[54],"task":[55],"due":[56],"the":[58,61,68,106,133,149,164,186,189],"sparsity":[59],"available":[62],"data":[63,134],"--":[64],"over":[65],"60%":[66],"city":[69],"are":[71,182],"unknown":[72],"their":[74],"records.":[76],"To":[77,117],"address":[78],"problem,":[80],"incorporate":[82],"another":[83],"human":[87],"lifestyles,":[88,193],"namely":[89],"mobility":[90],"With":[92],"on":[94,152,159],"\"where":[95],"go\",":[97],"infer":[99],"\"what":[100],"buy\".":[102],"Moreover,":[103],"model":[105,128,147],"relations":[107],"between":[108,188],"regions,":[109,170],"exploit":[111],"spatial":[112],"interactions":[113],"our":[115,146],"method.":[116],"that":[118,145],"end,":[119],"Collective":[120],"Matrix":[121],"Factorization":[122],"(CMF)":[123],"with":[124],"interaction":[126],"regularization":[127],"applied":[130],"fuse":[132],"from":[135],"multiple":[136,160],"views":[137,191],"sources.":[139],"Our":[140,156],"experimental":[141],"results":[142,158],"have":[143],"shown":[144],"outperforms":[148],"baseline":[150],"methods":[151],"two":[153,190],"standard":[154],"metrics.":[155],"prediction":[157],"reveal":[163],"divergent":[165],"demands":[166],"thus":[172],"reflect":[173],"key":[174],"functional":[175],"characteristics":[176],"city.":[179],"Furthermore,":[180],"able":[183],"extract":[185],"connection":[187],"achieve":[195],"novel":[199]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}