{"id":"https://openalex.org/W7128534846","doi":"https://doi.org/10.48550/arxiv.2602.08886","title":"Contrastive Learning for Diversity-Aware Product Recommendations in Retail","display_name":"Contrastive Learning for Diversity-Aware Product Recommendations in Retail","publication_year":2026,"publication_date":"2026-02-09","ids":{"openalex":"https://openalex.org/W7128534846","doi":"https://doi.org/10.48550/arxiv.2602.08886"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.08886","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.08886","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2602.08886","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076689139","display_name":"\u0392\u03b1\u03c3\u03af\u03bb\u03b5\u03b9\u03bf\u03c2 \u039a\u03b1\u03c1\u03bb\u03ae\u03c2","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karlis, Vasileios","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070927863","display_name":"Ezgi Y\u0131ld\u0131r\u0131m","orcid":"https://orcid.org/0000-0001-9684-5769"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Y\u0131ld\u0131r\u0131m, Ezgi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106343201","display_name":"David Vos","orcid":"https://orcid.org/0009-0003-8925-1585"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vos, David","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125583400","display_name":"Maarten de Rijke","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"de Rijke, Maarten","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.847599983215332,"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":0.847599983215332,"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":0.02319999970495701,"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/T11644","display_name":"Spam and Phishing Detection","score":0.012199999764561653,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.6980999708175659},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6818000078201294},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.6725999712944031},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.6291000247001648},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6169999837875366},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5835999846458435}],"concepts":[{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.6980999708175659},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6818000078201294},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6808000206947327},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.6725999712944031},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.6291000247001648},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6169999837875366},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5835999846458435},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.38109999895095825},{"id":"https://openalex.org/C78597825","wikidata":"https://www.wikidata.org/wiki/Q484847","display_name":"E-commerce","level":2,"score":0.36489999294281006},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3598000109195709},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.35359999537467957},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3294999897480011},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3271999955177307},{"id":"https://openalex.org/C192314503","wikidata":"https://www.wikidata.org/wiki/Q780705","display_name":"Digital native","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C23219732","wikidata":"https://www.wikidata.org/wiki/Q7247800","display_name":"Product type","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C2780102126","wikidata":"https://www.wikidata.org/wiki/Q10928179","display_name":"Online and offline","level":2,"score":0.2535000145435333}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.08886","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.08886","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2602.08886","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.08886","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4857349693775177,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recommender":[0],"systems":[1],"often":[2],"struggle":[3],"with":[4,31,75],"long-tail":[5],"distributions":[6],"and":[7,33,82],"limited":[8],"item":[9],"catalog":[10,44,91],"exposure,":[11],"where":[12],"a":[13,94],"small":[14],"subset":[15],"of":[16,98],"popular":[17],"items":[18],"dominates":[19],"recommendations.":[20],"This":[21,37],"challenge":[22],"is":[23],"especially":[24],"critical":[25],"in":[26,50,64],"large-scale":[27],"online":[28,83],"retail":[29],"settings":[30],"extensive":[32],"diverse":[34,96],"product":[35],"assortments.":[36],"paper":[38],"introduces":[39],"an":[40],"approach":[41],"to":[42,67],"enhance":[43],"coverage":[45],"without":[46],"compromising":[47],"recommendation":[48,54,103],"quality":[49],"the":[51],"existing":[52],"digital":[53],"pipeline":[55],"at":[56],"IKEA":[57],"Retail.":[58],"Drawing":[59],"inspiration":[60],"from":[61],"recent":[62],"advances":[63],"negative":[65,78],"sampling":[66],"address":[68],"popularity":[69],"bias,":[70],"we":[71,85],"integrate":[72],"contrastive":[73],"learning":[74],"carefully":[76],"selected":[77],"samples.":[79],"Through":[80],"offline":[81],"evaluations,":[84],"demonstrate":[86],"that":[87],"our":[88],"method":[89],"improves":[90],"coverage,":[92],"ensuring":[93],"more":[95],"set":[97],"recommendations":[99],"yet":[100],"preserving":[101],"strong":[102],"performance.":[104]},"counts_by_year":[],"updated_date":"2026-08-16T07:02:28.622633","created_date":"2026-02-11T00:00:00"}
