{"id":"https://openalex.org/W4296604434","doi":"https://doi.org/10.1145/3523227.3551477","title":"M2TRec: Metadata-aware Multi-task Transformer for Large-scale and Cold-start free Session-based Recommendations","display_name":"M2TRec: Metadata-aware Multi-task Transformer for Large-scale and Cold-start free Session-based Recommendations","publication_year":2022,"publication_date":"2022-09-13","ids":{"openalex":"https://openalex.org/W4296604434","doi":"https://doi.org/10.1145/3523227.3551477"},"language":"en","primary_location":{"id":"doi:10.1145/3523227.3551477","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3523227.3551477","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2209.11824","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102921373","display_name":"Walid Shalaby","orcid":"https://orcid.org/0000-0002-4407-8585"},"institutions":[{"id":"https://openalex.org/I2799939184","display_name":"Home Depot (United States)","ror":"https://ror.org/031603425","country_code":"US","type":"company","lineage":["https://openalex.org/I2799939184"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Walid Shalaby","raw_affiliation_strings":["The Home Depot, United States"],"affiliations":[{"raw_affiliation_string":"The Home Depot, United States","institution_ids":["https://openalex.org/I2799939184"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086691172","display_name":"Sejoon Oh","orcid":"https://orcid.org/0000-0002-0295-2756"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sejoon Oh","raw_affiliation_strings":["School of Computational Science and Engineering, Georgia Institute of Technology, United States"],"affiliations":[{"raw_affiliation_string":"School of Computational Science and Engineering, Georgia Institute of Technology, United States","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068120387","display_name":"Amir Afsharinejad","orcid":"https://orcid.org/0000-0002-9754-2716"},"institutions":[{"id":"https://openalex.org/I2799939184","display_name":"Home Depot (United States)","ror":"https://ror.org/031603425","country_code":"US","type":"company","lineage":["https://openalex.org/I2799939184"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amir Afsharinejad","raw_affiliation_strings":["The Home Depot, United States"],"affiliations":[{"raw_affiliation_string":"The Home Depot, United States","institution_ids":["https://openalex.org/I2799939184"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056142478","display_name":"Srijan Kumar","orcid":"https://orcid.org/0000-0002-5796-3532"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Srijan Kumar","raw_affiliation_strings":["School of Computational Science and Engineering, Georgia Institute of Technology, United States"],"affiliations":[{"raw_affiliation_string":"School of Computational Science and Engineering, Georgia Institute of Technology, United States","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102967365","display_name":"Xiquan Cui","orcid":"https://orcid.org/0009-0005-5306-8839"},"institutions":[{"id":"https://openalex.org/I2799939184","display_name":"Home Depot (United States)","ror":"https://ror.org/031603425","country_code":"US","type":"company","lineage":["https://openalex.org/I2799939184"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiquan Cui","raw_affiliation_strings":["The Home Depot, United States"],"affiliations":[{"raw_affiliation_string":"The Home Depot, United States","institution_ids":["https://openalex.org/I2799939184"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102921373"],"corresponding_institution_ids":["https://openalex.org/I2799939184"],"apc_list":null,"apc_paid":null,"fwci":7.0021,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.970633,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"573","last_page":"578"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T10028","display_name":"Topic Modeling","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9887999892234802,"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/metadata","display_name":"Metadata","score":0.8629653453826904},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7954052686691284},{"id":"https://openalex.org/keywords/session","display_name":"Session (web analytics)","score":0.7418420910835266},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6119154691696167},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6021870374679565},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5900388956069946},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5788853168487549},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5125250816345215},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4754452407360077},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.40153083205223083},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3769606351852417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3721740245819092},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.22022810578346252},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.13329440355300903}],"concepts":[{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.8629653453826904},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7954052686691284},{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.7418420910835266},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6119154691696167},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6021870374679565},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5900388956069946},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5788853168487549},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5125250816345215},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4754452407360077},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.40153083205223083},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3769606351852417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3721740245819092},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.22022810578346252},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.13329440355300903},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3523227.3551477","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3523227.3551477","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2209.11824","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2209.11824","pdf_url":"https://arxiv.org/pdf/2209.11824","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2209.11824","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2209.11824","pdf_url":"https://arxiv.org/pdf/2209.11824","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W2082927600","https://openalex.org/W2086511124","https://openalex.org/W2474765392","https://openalex.org/W2512965516","https://openalex.org/W2513020047","https://openalex.org/W2624871570","https://openalex.org/W2626454364","https://openalex.org/W2745534091","https://openalex.org/W2753328553","https://openalex.org/W2777210537","https://openalex.org/W2792643794","https://openalex.org/W2803744611","https://openalex.org/W2899457523","https://openalex.org/W2911946608","https://openalex.org/W2951369132","https://openalex.org/W2953586472","https://openalex.org/W2962784628","https://openalex.org/W2963669159","https://openalex.org/W2964044287","https://openalex.org/W2964199361","https://openalex.org/W2964926209","https://openalex.org/W2972941122","https://openalex.org/W2982275843","https://openalex.org/W3013802045","https://openalex.org/W3021402147","https://openalex.org/W3031331881","https://openalex.org/W3034329572","https://openalex.org/W3034427927","https://openalex.org/W3035588407","https://openalex.org/W3088983215","https://openalex.org/W3100538332","https://openalex.org/W3101707147","https://openalex.org/W3102619277","https://openalex.org/W3104492324","https://openalex.org/W3106433415","https://openalex.org/W3112334685","https://openalex.org/W3152513422","https://openalex.org/W3166827814","https://openalex.org/W3197173998","https://openalex.org/W3199647641","https://openalex.org/W3200585014","https://openalex.org/W3200664681","https://openalex.org/W3206932362","https://openalex.org/W3208349097","https://openalex.org/W3210938103","https://openalex.org/W4287080796","https://openalex.org/W4289488615","https://openalex.org/W4299286960","https://openalex.org/W4300175872","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W2058118494","https://openalex.org/W2392768766","https://openalex.org/W2382021449","https://openalex.org/W2095118173","https://openalex.org/W2106424170","https://openalex.org/W1985426483","https://openalex.org/W4206178588","https://openalex.org/W3094491777","https://openalex.org/W3214715529","https://openalex.org/W4287635093"],"abstract_inverted_index":{"Session-based":[0],"recommender":[1],"systems":[2],"(SBRSs)":[3],"have":[4,66,150],"shown":[5],"superior":[6],"performance":[7,43,68,205],"over":[8],"conventional":[9],"methods.":[10],"However,":[11],"they":[12,139],"show":[13,62,203],"limited":[14],"scalability":[15],"on":[16,44,69,211,214],"large-scale":[17],"industrial":[18,58],"datasets":[19],"since":[20],"most":[21],"models":[22],"learn":[23,108,118],"one":[24,37,53,56,109],"embedding":[25,110],"per":[26,39,111],"item.":[27],"This":[28],"leads":[29],"to":[30,96,107,117,172],"a":[31,78,90,169],"large":[32,57],"memory":[33],"requirement":[34],"(of":[35],"storing":[36],"vector":[38],"item)":[40],"and":[41,55,98,147,161,185,195],"poor":[42],"sparse":[45,70,73,162,212],"sessions":[46,71],"with":[47,72,141,153,181],"cold-start":[48,160],"or":[49,128],"unpopular":[50,129],"items.":[51,74,163],"Using":[52],"public":[54],"dataset,":[59],"we":[60],"experimentally":[61],"that":[63],"state-of-the-art":[64],"SBRSs":[65],"low":[67],"We":[75],"propose":[76],"M2TRec,":[77],"Metadata-aware":[79],"Multi-task":[80],"Transformer":[81],"model":[82,192],"for":[83,136],"session-based":[84],"recommendations.":[85],"Our":[86,187],"proposed":[87,209],"method":[88],"learns":[89],"transformation":[91],"function":[92],"from":[93],"item":[94,115,123,176],"metadata":[95,116],"embeddings,":[97],"is":[99,166],"thus,":[100],"item-ID":[101],"free":[102],"(i.e.,":[103],"does":[104],"not":[105],"need":[106],"item).":[112],"It":[113],"integrates":[114],"shared":[119],"representations":[120,135,152],"of":[121,158],"diverse":[122],"attributes.":[124],"During":[125],"inference,":[126],"new":[127],"items":[130,142,213],"will":[131,149],"be":[132],"assigned":[133],"identical":[134],"the":[137,174,178,191,198,215],"attributes":[138],"share":[140],"previously":[143],"observed":[144],"during":[145],"training,":[146],"thus":[148],"similar":[151],"those":[154],"items,":[155],"enabling":[156],"recommendations":[157],"even":[159],"Additionally,":[164],"M2TRec":[165],"trained":[167],"in":[168,177],"multi-task":[170,188],"setting":[171],"predict":[173],"next":[175],"session":[179],"along":[180],"its":[182],"primary":[183],"category":[184],"subcategories.":[186],"strategy":[189],"makes":[190],"converge":[193],"faster":[194],"significantly":[196],"improves":[197],"overall":[199],"performance.":[200],"Experimental":[201],"results":[202],"significant":[204],"gains":[206],"using":[207],"our":[208],"approach":[210],"two":[216],"datasets.":[217]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":7}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}