{"id":"https://openalex.org/W4317209674","doi":"https://doi.org/10.1145/3578710","title":"Don\u2019t Need All Eggs in One Basket: Reconstructing Composite Embeddings of Customers from Individual-Domain Embeddings","display_name":"Don\u2019t Need All Eggs in One Basket: Reconstructing Composite Embeddings of Customers from Individual-Domain Embeddings","publication_year":2023,"publication_date":"2023-01-18","ids":{"openalex":"https://openalex.org/W4317209674","doi":"https://doi.org/10.1145/3578710"},"language":"en","primary_location":{"id":"doi:10.1145/3578710","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3578710","pdf_url":null,"source":{"id":"https://openalex.org/S4210170305","display_name":"ACM Transactions on Management Information Systems","issn_l":"2158-656X","issn":["2158-656X","2158-6578"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Management Information Systems","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/A5011134797","display_name":"Moshe Unger","orcid":"https://orcid.org/0000-0001-5512-0331"},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Moshe Unger","raw_affiliation_strings":["Tel Aviv University, Israel"],"affiliations":[{"raw_affiliation_string":"Tel Aviv University, Israel","institution_ids":["https://openalex.org/I16391192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455171","display_name":"Pan Li","orcid":"https://orcid.org/0000-0001-6522-2446"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pan Li","raw_affiliation_strings":["Stern School of Business, New York University, USA"],"affiliations":[{"raw_affiliation_string":"Stern School of Business, New York University, USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025522057","display_name":"Sahana Sen","orcid":null},"institutions":[{"id":"https://openalex.org/I174216632","display_name":"City University of New York","ror":"https://ror.org/00453a208","country_code":"US","type":"education","lineage":["https://openalex.org/I174216632"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sahana (Shahana) Sen","raw_affiliation_strings":["BMCC, City University of New York, USA"],"affiliations":[{"raw_affiliation_string":"BMCC, City University of New York, USA","institution_ids":["https://openalex.org/I174216632"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016384155","display_name":"Alexander Tuzhilin","orcid":"https://orcid.org/0000-0003-3354-8462"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander Tuzhilin","raw_affiliation_strings":["Stern School of Business, New York University, USA"],"affiliations":[{"raw_affiliation_string":"Stern School of Business, New York University, USA","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5011134797"],"corresponding_institution_ids":["https://openalex.org/I16391192"],"apc_list":null,"apc_paid":null,"fwci":0.2277,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.551009,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"14","issue":"2","first_page":"1","last_page":"30"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6442303657531738},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5618889331817627},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.511991560459137},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4590742290019989},{"id":"https://openalex.org/keywords/composite-number","display_name":"Composite number","score":0.4465482234954834},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36550843715667725},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36422109603881836},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33017247915267944},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3292192220687866},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.23022153973579407},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1767635941505432}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6442303657531738},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5618889331817627},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.511991560459137},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4590742290019989},{"id":"https://openalex.org/C104779481","wikidata":"https://www.wikidata.org/wiki/Q50707","display_name":"Composite number","level":2,"score":0.4465482234954834},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36550843715667725},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36422109603881836},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33017247915267944},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3292192220687866},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.23022153973579407},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1767635941505432},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3578710","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3578710","pdf_url":null,"source":{"id":"https://openalex.org/S4210170305","display_name":"ACM Transactions on Management Information Systems","issn_l":"2158-656X","issn":["2158-656X","2158-6578"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Management Information Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":78,"referenced_works":["https://openalex.org/W592167830","https://openalex.org/W1557681559","https://openalex.org/W1562639377","https://openalex.org/W1924770834","https://openalex.org/W1967228352","https://openalex.org/W1971735090","https://openalex.org/W2009714216","https://openalex.org/W2038105990","https://openalex.org/W2047253786","https://openalex.org/W2054141820","https://openalex.org/W2064675550","https://openalex.org/W2100310563","https://openalex.org/W2100495367","https://openalex.org/W2103496339","https://openalex.org/W2108630796","https://openalex.org/W2109121923","https://openalex.org/W2118023920","https://openalex.org/W2123816765","https://openalex.org/W2137983211","https://openalex.org/W2148143831","https://openalex.org/W2150778199","https://openalex.org/W2157331557","https://openalex.org/W2157881433","https://openalex.org/W2167651543","https://openalex.org/W2171960770","https://openalex.org/W2200988052","https://openalex.org/W2281865947","https://openalex.org/W2345091005","https://openalex.org/W2396526128","https://openalex.org/W2407712691","https://openalex.org/W2422895071","https://openalex.org/W2473418344","https://openalex.org/W2518224431","https://openalex.org/W2604244600","https://openalex.org/W2605350416","https://openalex.org/W2749733699","https://openalex.org/W2766736793","https://openalex.org/W2768181417","https://openalex.org/W2781636776","https://openalex.org/W2784777439","https://openalex.org/W2788728386","https://openalex.org/W2797542337","https://openalex.org/W2803718882","https://openalex.org/W2886209086","https://openalex.org/W2915942816","https://openalex.org/W2929803724","https://openalex.org/W2963367478","https://openalex.org/W2965744319","https://openalex.org/W2965898633","https://openalex.org/W2966501701","https://openalex.org/W2977251589","https://openalex.org/W2984100107","https://openalex.org/W2996891863","https://openalex.org/W3004495293","https://openalex.org/W3011727199","https://openalex.org/W3028967430","https://openalex.org/W3038738925","https://openalex.org/W3081095512","https://openalex.org/W3088072029","https://openalex.org/W3100480425","https://openalex.org/W3107396745","https://openalex.org/W3109094166","https://openalex.org/W3112787034","https://openalex.org/W3123459983","https://openalex.org/W3123816264","https://openalex.org/W3124675547","https://openalex.org/W3141796648","https://openalex.org/W3157784591","https://openalex.org/W3177361862","https://openalex.org/W3184694980","https://openalex.org/W3215053434","https://openalex.org/W4235730356","https://openalex.org/W4243684872","https://openalex.org/W4255962414","https://openalex.org/W4290944002","https://openalex.org/W4299286960","https://openalex.org/W4299679152","https://openalex.org/W6692935382"],"related_works":["https://openalex.org/W2047973478","https://openalex.org/W4295532600","https://openalex.org/W2063823869","https://openalex.org/W2067569035","https://openalex.org/W2090985514","https://openalex.org/W4375867731","https://openalex.org/W2885323543","https://openalex.org/W2611989081","https://openalex.org/W2145649715","https://openalex.org/W2220635983"],"abstract_inverted_index":{"Although":[0],"building":[1,100],"a":[2,7,11,70],"360-degree":[3],"comprehensive":[4],"view":[5],"of":[6,46,128],"customer":[8,29,48,60,67,95,103,122,139],"has":[9,18],"been":[10,20],"long-standing":[12],"goal":[13],"in":[14,23,50,78,169],"marketing,":[15],"this":[16,51],"challenge":[17],"not":[19,151],"successfully":[21],"addressed":[22],"many":[24],"marketing":[25],"applications":[26,112],"because":[27],"fractured":[28],"data":[30,96],"stored":[31],"across":[32],"different":[33],"\u201csilos\u201d":[34],"are":[35],"hard":[36],"to":[37,55,89,113],"integrate":[38,56],"under":[39],"\u201cone":[40],"roof\u201d":[41],"for":[42,99],"several":[43,57],"reasons.":[44],"Instead":[45],"integrating":[47,135],"data,":[49],"article":[52],"we":[53,142],"propose":[54],"domain-specific":[58,92],"partial":[59,164],"views":[61],"into":[62],"one":[63],"consolidated":[64],"or":[65,93],"composite":[66,121,131,149],"profile":[68],"using":[69],"Deep":[71],"Learning-based":[72],"method":[73,87,117],"that":[74,115,124,144],"is":[75],"theoretically":[76],"grounded":[77],"Kolmogorov\u2019s":[79],"Mapping":[80],"Neural":[81],"Network":[82],"Existence":[83],"Theorem.":[84],"Furthermore,":[85],"our":[86,116],"needs":[88],"securely":[90],"access":[91],"siloed":[94,137],"only":[97,152],"once":[98],"the":[101,129,136,157],"initial":[102],"embeddings.":[104],"We":[105],"conduct":[106],"extensive":[107],"studies":[108],"on":[109],"two":[110],"industrial":[111],"demonstrate":[114],"effectively":[118],"reconstructs":[119],"stable":[120],"embeddings":[123,132,150,160,165],"constitute":[125],"strong":[126],"approximations":[127],"ground-truth":[130,159],"obtained":[133],"from":[134],"raw":[138],"data.":[140],"Moreover,":[141],"show":[143],"these":[145],"data-security":[146],"preserving":[147],"reconstructed":[148],"perform":[153],"as":[154,156],"well":[155],"original":[158],"but":[161],"significantly":[162],"outperform":[163],"and":[166,171],"state-of-the-art":[167],"baselines":[168],"recommendation":[170],"consumer":[172],"preference":[173],"prediction":[174],"tasks.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
