{"id":"https://openalex.org/W3156963027","doi":"https://doi.org/10.1109/tkde.2021.3074395","title":"Dual Metric Learning for Effective and Efficient Cross-Domain Recommendations","display_name":"Dual Metric Learning for Effective and Efficient Cross-Domain Recommendations","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3156963027","doi":"https://doi.org/10.1109/tkde.2021.3074395","mag":"3156963027"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2021.3074395","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3074395","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/A5017608553","display_name":"Li Pan","orcid":"https://orcid.org/0000-0001-8520-0842"},"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":true,"raw_author_name":"Pan Li","raw_affiliation_strings":["Technology, Operation and Statistics, New York University Stern School of Business, 5893 New York, New York, United States, (e-mail: pli2@stern.nyu.edu)"],"affiliations":[{"raw_affiliation_string":"Technology, Operation and Statistics, New York University Stern School of Business, 5893 New York, New York, United States, (e-mail: pli2@stern.nyu.edu)","institution_ids":["https://openalex.org/I57206974"]}]},{"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/I4210155590","display_name":"Management Sciences (United States)","ror":"https://ror.org/05shz5j84","country_code":"US","type":"company","lineage":["https://openalex.org/I4210155590"]},{"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":["Information, Operations & Management Sciences, New York University, New York, New York, United States, 10012-1126 (e-mail: atuzhili@stern.nyu.edu)"],"affiliations":[{"raw_affiliation_string":"Information, Operations & Management Sciences, New York University, New York, New York, United States, 10012-1126 (e-mail: atuzhili@stern.nyu.edu)","institution_ids":["https://openalex.org/I57206974","https://openalex.org/I4210155590"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5017608553"],"corresponding_institution_ids":["https://openalex.org/I57206974"],"apc_list":null,"apc_paid":null,"fwci":12.1179,"has_fulltext":false,"cited_by_count":67,"citation_normalized_percentile":{"value":0.98569257,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":1.0,"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":0.979200005531311,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9743000268936157,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.8782630562782288},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.7670180797576904},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.7041994333267212},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.6472204923629761},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6281452178955078},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.537481427192688},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.47520551085472107},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4725189805030823},{"id":"https://openalex.org/keywords/performance-metric","display_name":"Performance metric","score":0.41816896200180054},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3848688006401062},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.33296966552734375}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8782630562782288},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7670180797576904},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.7041994333267212},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.6472204923629761},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6281452178955078},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.537481427192688},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.47520551085472107},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4725189805030823},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.41816896200180054},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3848688006401062},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.33296966552734375},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2021.3074395","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3074395","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":[{"display_name":"Industry, innovation and infrastructure","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":98,"referenced_works":["https://openalex.org/W143867266","https://openalex.org/W163868085","https://openalex.org/W1486317198","https://openalex.org/W1720514416","https://openalex.org/W1836465849","https://openalex.org/W1959608418","https://openalex.org/W1989318262","https://openalex.org/W2052087587","https://openalex.org/W2057171152","https://openalex.org/W2071018795","https://openalex.org/W2096943734","https://openalex.org/W2111138053","https://openalex.org/W2111286903","https://openalex.org/W2117154949","https://openalex.org/W2117420919","https://openalex.org/W2118674552","https://openalex.org/W2130942839","https://openalex.org/W2131241448","https://openalex.org/W2132538571","https://openalex.org/W2135029798","https://openalex.org/W2140376886","https://openalex.org/W2143374704","https://openalex.org/W2157881433","https://openalex.org/W2158515176","https://openalex.org/W2161047120","https://openalex.org/W2165698076","https://openalex.org/W2171960770","https://openalex.org/W2205235818","https://openalex.org/W2253995343","https://openalex.org/W2398879410","https://openalex.org/W2405459681","https://openalex.org/W2546938941","https://openalex.org/W2600538886","https://openalex.org/W2604433096","https://openalex.org/W2605350416","https://openalex.org/W2612388534","https://openalex.org/W2725606191","https://openalex.org/W2733239165","https://openalex.org/W2752210368","https://openalex.org/W2782259251","https://openalex.org/W2783565819","https://openalex.org/W2785093437","https://openalex.org/W2796608345","https://openalex.org/W2807021761","https://openalex.org/W2809291355","https://openalex.org/W2903803738","https://openalex.org/W2904156528","https://openalex.org/W2906684937","https://openalex.org/W2906995678","https://openalex.org/W2907206525","https://openalex.org/W2912073028","https://openalex.org/W2913488954","https://openalex.org/W2949920370","https://openalex.org/W2963085847","https://openalex.org/W2963746531","https://openalex.org/W2964159782","https://openalex.org/W2971196067","https://openalex.org/W2973142485","https://openalex.org/W2986176093","https://openalex.org/W2987679642","https://openalex.org/W2996891863","https://openalex.org/W2998128907","https://openalex.org/W3026319246","https://openalex.org/W3028156525","https://openalex.org/W3088072029","https://openalex.org/W3098400049","https://openalex.org/W3099026360","https://openalex.org/W3100591234","https://openalex.org/W3100848837","https://openalex.org/W3103897518","https://openalex.org/W3122722458","https://openalex.org/W3136403187","https://openalex.org/W4210880854","https://openalex.org/W4242223475","https://openalex.org/W4288083766","https://openalex.org/W4293568373","https://openalex.org/W4299286960","https://openalex.org/W4299679152","https://openalex.org/W4301621763","https://openalex.org/W6605917969","https://openalex.org/W6638667902","https://openalex.org/W6640963894","https://openalex.org/W6676794045","https://openalex.org/W6677328822","https://openalex.org/W6678911119","https://openalex.org/W6679436768","https://openalex.org/W6680012447","https://openalex.org/W6680832709","https://openalex.org/W6688089849","https://openalex.org/W6692935382","https://openalex.org/W6713708190","https://openalex.org/W6729383884","https://openalex.org/W6731682836","https://openalex.org/W6740590407","https://openalex.org/W6743566960","https://openalex.org/W6745535286","https://openalex.org/W6780248173","https://openalex.org/W7064683377"],"related_works":["https://openalex.org/W2935370024","https://openalex.org/W4361804730","https://openalex.org/W2142113611","https://openalex.org/W2018387840","https://openalex.org/W2087870008","https://openalex.org/W2162534555","https://openalex.org/W2045629210","https://openalex.org/W2143024819","https://openalex.org/W2107419853","https://openalex.org/W2334467465"],"abstract_inverted_index":{"Cross":[0],"domain":[1],"recommender":[2],"systems":[3],"have":[4],"been":[5],"increasingly":[6],"valuable":[7],"for":[8],"helping":[9],"consumers":[10],"identify":[11],"useful":[12],"items":[13,62],"in":[14,34,72,93],"different":[15,122],"applications.":[16,36],"However,":[17],"existing":[18],"cross-domain":[19,47,79,157],"models":[20],"typically":[21],"require":[22],"large":[23],"number":[24],"of":[25,46],"overlap":[26,147,193,207],"users,":[27],"which":[28,137],"can":[29],"be":[30],"difficult":[31],"to":[32,52,109,140,154,195,200],"obtain":[33,196],"some":[35],"In":[37],"addition,":[38],"they":[39],"did":[40],"not":[41],"consider":[42],"the":[43,98,128,133,143,149,162,178,185,201],"duality":[44],"structure":[45],"recommendation":[48,66,80,158,197],"tasks,":[49],"thus":[50],"failing":[51],"take":[53],"into":[54],"account":[55],"bidirectional":[56],"latent":[57,106,123],"relations":[58,118],"between":[59,89,119],"users":[60,120,194],"and":[61,63,152,170,175],"achieve":[64],"optimal":[65],"performance.":[67,159],"To":[68],"address":[69],"these":[70],"issues,":[71],"this":[73],"paper":[74],"we":[75,126],"propose":[76],"a":[77,104],"novel":[78,105],"model":[81,164,187],"based":[82],"on":[83,165],"dual":[84,129],"learning":[85,99,130,135],"that":[86,172,184,204],"transfers":[87],"information":[88],"two":[90,150],"related":[91],"domains":[92,115,151],"an":[94],"iterative":[95],"manner":[96],"until":[97],"process":[100],"stabilizes.":[101],"We":[102,160,181],"develop":[103],"orthogonal":[107],"mapping":[108],"extract":[110],"user":[111,146],"preferences":[112],"over":[113],"multiple":[114],"while":[116],"preserving":[117],"across":[121,148],"spaces.":[124],"Furthermore,":[125],"combine":[127],"method":[131],"with":[132,190],"metric":[134],"approach,":[136],"allows":[138],"us":[139],"significantly":[141,176],"reduce":[142],"required":[144],"common":[145],"leads":[153],"even":[155],"better":[156],"test":[161],"proposed":[163,186],"three":[166],"large-scale":[167],"industrial":[168],"datasets":[169],"demonstrate":[171],"it":[173],"consistently":[174],"outperforms":[177],"state-of-the-art":[179,202],"baselines.":[180],"also":[182],"show":[183],"works":[188],"well":[189],"very":[191],"few":[192],"performance":[198],"comparable":[199],"baselines":[203],"use":[205],"many":[206],"users.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":22},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}