{"id":"https://openalex.org/W4406258578","doi":"https://doi.org/10.1109/tkde.2024.3452638","title":"Contextual Inference From Sparse Shopping Transactions Based on Motif Patterns","display_name":"Contextual Inference From Sparse Shopping Transactions Based on Motif Patterns","publication_year":2025,"publication_date":"2025-01-10","ids":{"openalex":"https://openalex.org/W4406258578","doi":"https://doi.org/10.1109/tkde.2024.3452638"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2024.3452638","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2024.3452638","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"},"type":"article","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/A5037854753","display_name":"Jiayun Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jiayun Zhang","raw_affiliation_strings":["Department of Computer Science and Engineering, Halicioglu Data Science Institute, University of California, La Jolla, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Halicioglu Data Science Institute, University of California, La Jolla, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022999126","display_name":"Xinyang Zhang","orcid":"https://orcid.org/0000-0001-6474-682X"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinyang Zhang","raw_affiliation_strings":["Department of Computer Science, University of Illinois at Urbana-Champaign, Champaign, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois at Urbana-Champaign, Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088730125","display_name":"Dezhi Hong","orcid":"https://orcid.org/0000-0001-5224-6043"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dezhi Hong","raw_affiliation_strings":["Department of Computer Science and Engineering, Halicioglu Data Science Institute, University of California, La Jolla, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Halicioglu Data Science Institute, University of California, La Jolla, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078959213","display_name":"Rajesh K. Gupta","orcid":"https://orcid.org/0000-0002-6489-7633"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rajesh K. Gupta","raw_affiliation_strings":["Department of Computer Science and Engineering, Halicioglu Data Science Institute, University of California, La Jolla, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Halicioglu Data Science Institute, University of California, La Jolla, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039500313","display_name":"Jingbo Shang","orcid":"https://orcid.org/0000-0002-7249-4404"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingbo Shang","raw_affiliation_strings":["Department of Computer Science and Engineering, Halicioglu Data Science Institute, University of California, La Jolla, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Halicioglu Data Science Institute, University of California, La Jolla, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5037854753"],"corresponding_institution_ids":["https://openalex.org/I36258959"],"apc_list":null,"apc_paid":null,"fwci":2.1794,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.83610006,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"37","issue":"2","first_page":"572","last_page":"583"},"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":0.941100001335144,"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":0.941100001335144,"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/T11942","display_name":"Transportation and Mobility Innovations","score":0.9370999932289124,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9287999868392944,"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/motif","display_name":"Motif (music)","score":0.7707930207252502},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7700995802879333},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7597617506980896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41150805354118347},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3431417942047119},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3415359854698181}],"concepts":[{"id":"https://openalex.org/C32276052","wikidata":"https://www.wikidata.org/wiki/Q908349","display_name":"Motif (music)","level":2,"score":0.7707930207252502},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7700995802879333},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7597617506980896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41150805354118347},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3431417942047119},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3415359854698181},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2024.3452638","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2024.3452638","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W41368942","https://openalex.org/W797227816","https://openalex.org/W1548361610","https://openalex.org/W1988116328","https://openalex.org/W2000764607","https://openalex.org/W2028485238","https://openalex.org/W2029917036","https://openalex.org/W2030214288","https://openalex.org/W2037417802","https://openalex.org/W2053890456","https://openalex.org/W2065130322","https://openalex.org/W2081456048","https://openalex.org/W2099216531","https://openalex.org/W2149684865","https://openalex.org/W2152755144","https://openalex.org/W2153624566","https://openalex.org/W2168175183","https://openalex.org/W2268305941","https://openalex.org/W2329516605","https://openalex.org/W2481071203","https://openalex.org/W2743104969","https://openalex.org/W2906831717","https://openalex.org/W2906877346","https://openalex.org/W2963953172","https://openalex.org/W2967121697","https://openalex.org/W2993175137","https://openalex.org/W2999693458","https://openalex.org/W3023960840","https://openalex.org/W3043239945","https://openalex.org/W3080152140","https://openalex.org/W3081199790","https://openalex.org/W3099053576","https://openalex.org/W4294170691","https://openalex.org/W4322718576","https://openalex.org/W4385245566","https://openalex.org/W6639055396","https://openalex.org/W6685125189","https://openalex.org/W6726873649","https://openalex.org/W6729323343","https://openalex.org/W6746782004","https://openalex.org/W6857925552"],"related_works":["https://openalex.org/W3170299350","https://openalex.org/W2368410102","https://openalex.org/W2605676258","https://openalex.org/W2368037387","https://openalex.org/W190186656","https://openalex.org/W2902352756","https://openalex.org/W2377079823","https://openalex.org/W2953439652","https://openalex.org/W2599962286","https://openalex.org/W2319582300"],"abstract_inverted_index":{"Inferring":[0],"contextual":[1],"information":[2,40],"such":[3],"as":[4,121],"demographics":[5,182],"from":[6,46,75],"historical":[7,43],"transactions":[8,30,45],"is":[9,177],"valuable":[10],"to":[11,70,87,100,106],"public":[12,56],"agencies":[13],"and":[14,20,78,123,144,163,169],"businesses.":[15],"Existing":[16],"methods":[17],"are":[18,31],"data-hungry":[19],"do":[21],"not":[22],"work":[23],"well":[24],"when":[25],"the":[26,148,152,198],"available":[27],"records":[28],"of":[29,38,114,160,165,179,192],"sparse.":[32],"We":[33,61,91,150],"consider":[34],"here":[35],"specifically":[36],"inference":[37],"demographic":[39,89,108],"using":[41,116,183],"limited":[42],"grocery":[44,194],"a":[47,52,63,72,94,125,185],"few":[48],"random":[49,193],"trips":[50],"that":[51,84,173],"typical":[53],"business":[54],"or":[55],"service":[57],"organization":[58],"may":[59],"see.":[60],"propose":[62],"novel":[64,95],"method":[65],"called":[66],"<sc":[67,174],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[68,175],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">DemoMotif</small>":[69,176],"build":[71],"network":[73],"model":[74],"heterogeneous":[76],"data":[77],"identify":[79],"subgraph":[80],"patterns":[81],"(i.e.,":[82],"motifs)":[83],"enable":[85],"us":[86],"infer":[88],"attributes.":[90],"then":[92],"design":[93],"motif":[96,119],"context":[97],"selection":[98],"algorithm":[99],"find":[101],"specific":[102],"node":[103],"combinations":[104],"significant":[105],"certain":[107],"groups.":[109],"Finally,":[110],"we":[111,135],"learn":[112],"representations":[113],"households":[115],"these":[117],"selected":[118],"instances":[120],"context,":[122],"employ":[124],"standard":[126],"classifier":[127],"(e.g.,":[128,188],"SVM)":[129],"for":[130,154],"inference.":[131],"For":[132],"evaluation":[133],"purposes,":[134],"use":[136],"three":[137,156],"real-world":[138],"consumer":[139],"datasets,":[140],"spanning":[141],"different":[142],"regions":[143],"time":[145],"periods":[146],"in":[147],"U.S.":[149],"evaluate":[151],"framework":[153],"predicting":[155],"attributes:":[157],"ethnicity,":[158],"seniority":[159],"household":[161,181],"heads,":[162],"presence":[164],"children.":[166],"Extensive":[167],"experiments":[168],"case":[170],"studies":[171],"demonstrate":[172],"capable":[178],"inferring":[180],"only":[184],"small":[186],"number":[187],"fewer":[189],"than":[190],"10)":[191],"trips,":[195],"significantly":[196],"outperforming":[197],"state-of-the-art.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
