{"id":"https://openalex.org/W4224110370","doi":"https://doi.org/10.1145/3523227.3546777","title":"Context and Attribute-Aware Sequential Recommendation via Cross-Attention","display_name":"Context and Attribute-Aware Sequential Recommendation via Cross-Attention","publication_year":2022,"publication_date":"2022-09-13","ids":{"openalex":"https://openalex.org/W4224110370","doi":"https://doi.org/10.1145/3523227.3546777"},"language":"en","primary_location":{"id":"doi:10.1145/3523227.3546777","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3523227.3546777","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/2204.06519","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053107270","display_name":"Ahmed Nabih Zaki Rashed","orcid":"https://orcid.org/0000-0002-5338-1623"},"institutions":[{"id":"https://openalex.org/I155765044","display_name":"University of Hildesheim","ror":"https://ror.org/02f9det96","country_code":"DE","type":"education","lineage":["https://openalex.org/I155765044"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Ahmed Rashed","raw_affiliation_strings":["Information Systems and Machine Learning Lab, University of Hildesheim, Germany"],"affiliations":[{"raw_affiliation_string":"Information Systems and Machine Learning Lab, University of Hildesheim, Germany","institution_ids":["https://openalex.org/I155765044"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101704435","display_name":"Shereen H. Elsayed","orcid":"https://orcid.org/0000-0001-5110-2961"},"institutions":[{"id":"https://openalex.org/I155765044","display_name":"University of Hildesheim","ror":"https://ror.org/02f9det96","country_code":"DE","type":"education","lineage":["https://openalex.org/I155765044"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Shereen Elsayed","raw_affiliation_strings":["Information Systems and Machine Learning Lab, University of Hildesheim, Germany"],"affiliations":[{"raw_affiliation_string":"Information Systems and Machine Learning Lab, University of Hildesheim, Germany","institution_ids":["https://openalex.org/I155765044"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039470755","display_name":"Lars Schmidt-Thieme","orcid":"https://orcid.org/0000-0001-5729-6023"},"institutions":[{"id":"https://openalex.org/I155765044","display_name":"University of Hildesheim","ror":"https://ror.org/02f9det96","country_code":"DE","type":"education","lineage":["https://openalex.org/I155765044"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Lars Schmidt-Thieme","raw_affiliation_strings":["Institute for Computer Science, University of Hildesheim, Germany"],"affiliations":[{"raw_affiliation_string":"Institute for Computer Science, University of Hildesheim, Germany","institution_ids":["https://openalex.org/I155765044"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5053107270"],"corresponding_institution_ids":["https://openalex.org/I155765044"],"apc_list":null,"apc_paid":null,"fwci":22.9717,"has_fulltext":false,"cited_by_count":79,"citation_normalized_percentile":{"value":0.99536903,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"71","last_page":"80"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.983299970626831,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9492999911308289,"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":0.8539140820503235},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.8395249247550964},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.7276200652122498},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5620079636573792},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5216569900512695},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.47795820236206055},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4773333668708801},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4655713737010956},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.41579577326774597},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.18944451212882996}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8539140820503235},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8395249247550964},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.7276200652122498},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5620079636573792},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5216569900512695},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.47795820236206055},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4773333668708801},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4655713737010956},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.41579577326774597},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.18944451212882996},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3523227.3546777","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3523227.3546777","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:2204.06519","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2204.06519","pdf_url":"https://arxiv.org/pdf/2204.06519","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:2204.06519","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2204.06519","pdf_url":"https://arxiv.org/pdf/2204.06519","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W2038585576","https://openalex.org/W2095705004","https://openalex.org/W2108598243","https://openalex.org/W2140310134","https://openalex.org/W2194775991","https://openalex.org/W2295739661","https://openalex.org/W2604662567","https://openalex.org/W2613725451","https://openalex.org/W2626454364","https://openalex.org/W2723293840","https://openalex.org/W2750779823","https://openalex.org/W2767724106","https://openalex.org/W2896457183","https://openalex.org/W2898085636","https://openalex.org/W2912745432","https://openalex.org/W2937556626","https://openalex.org/W2945940573","https://openalex.org/W2951645301","https://openalex.org/W2957191877","https://openalex.org/W2962745591","https://openalex.org/W2963323306","https://openalex.org/W2963367478","https://openalex.org/W2963655167","https://openalex.org/W2964052347","https://openalex.org/W2965398302","https://openalex.org/W2966483207","https://openalex.org/W2973090653","https://openalex.org/W2984100107","https://openalex.org/W2996931760","https://openalex.org/W2997878072","https://openalex.org/W3005071803","https://openalex.org/W3035666843","https://openalex.org/W3044549925","https://openalex.org/W3065542300","https://openalex.org/W3088235863","https://openalex.org/W3100260481","https://openalex.org/W3100446379","https://openalex.org/W3101704389","https://openalex.org/W3101708421","https://openalex.org/W3102619277","https://openalex.org/W3105114834","https://openalex.org/W4231054948","https://openalex.org/W4239072543","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W4390273403","https://openalex.org/W4386781444","https://openalex.org/W2150182025","https://openalex.org/W3092950680","https://openalex.org/W3197542405","https://openalex.org/W2056712470","https://openalex.org/W3125580266","https://openalex.org/W4288390103","https://openalex.org/W4317039510","https://openalex.org/W2954428433"],"abstract_inverted_index":{"In":[0,44],"sparse":[1],"recommender":[2,57,168,212],"settings,":[3],"users\u2019":[4],"context":[5,54],"and":[6,26,55,75,87,114,128,147,154,187,200],"item":[7,76,89,99,160,185],"attributes":[8,77,218],"play":[9],"a":[10,53,104,221,225],"crucial":[11],"role":[12],"in":[13,24,70,150,181,194,224],"deciding":[14,158],"which":[15,159],"items":[16,117,127,131,149],"to":[17,132,141,161,192],"recommend":[18,162],"next.":[19,163],"Despite":[20],"that,":[21],"recent":[22,110,148],"works":[23],"sequential":[25,98],"time-aware":[27],"recommendations":[28],"usually":[29],"either":[30],"ignore":[31],"both":[32],"aspects":[33],"or":[34],"only":[35],"consider":[36],"one":[37],"of":[38,66,72,94,184,190],"them,":[39],"limiting":[40],"their":[41,134,155],"predictive":[42],"performance.":[43],"this":[45],"paper,":[46],"we":[47],"address":[48],"these":[49],"limitations":[50],"by":[51,214],"proposing":[52],"attribute-aware":[56],"model":[58,175],"(CARCA)":[59],"that":[60,83,102,172,205],"can":[61],"capture":[62],"the":[63,67,95,108,115,129,143,151,173,182],"dynamic":[64],"nature":[65],"user":[68,152],"profiles":[69],"terms":[71],"contextual":[73],"features":[74,86,113],"via":[78],"dedicated":[79,210],"multi-head":[80],"self-attention":[81],"blocks":[82],"extract":[84],"profile-level":[85],"predict":[88,133],"scores.":[90,136],"Also,":[91],"unlike":[92],"many":[93],"current":[96],"state-of-the-art":[97,179,209],"recommendation":[100,186],"approaches":[101],"use":[103],"simple":[105],"dot-product":[106],"between":[107,124,145],"most":[109],"item\u2019s":[111],"latent":[112],"target":[116,130],"embeddings":[118],"for":[119],"scoring,":[120],"CARCA":[121,140,206],"uses":[122],"cross-attention":[123,138],"all":[125,178],"profile":[126,153],"final":[135],"This":[137],"allows":[139],"harness":[142],"correlation":[144],"old":[146],"influence":[156],"on":[157,165],"Experiments":[164],"four":[166],"real-world":[167],"system":[169],"datasets":[170],"show":[171,204],"proposed":[174],"significantly":[176],"outperforms":[177],"models":[180],"task":[183],"achieving":[188],"improvements":[189],"up":[191],"53%":[193],"Normalized":[195],"Discounted":[196],"Cumulative":[197],"Gain":[198],"(NDCG)":[199],"Hit-Ratio.":[201],"Results":[202],"also":[203],"outperformed":[207],"several":[208],"image-based":[211],"systems":[213],"merely":[215],"utilizing":[216],"image":[217],"extracted":[219],"from":[220],"pre-trained":[222],"ResNet50":[223],"black-box":[226],"fashion.":[227]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":34},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":19},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-23T09:07:50.710637","created_date":"2022-04-19T00:00:00"}
