{"id":"https://openalex.org/W4386729001","doi":"https://doi.org/10.1145/3604915.3608830","title":"Incorporating Time in Sequential Recommendation Models","display_name":"Incorporating Time in Sequential Recommendation Models","publication_year":2023,"publication_date":"2023-09-14","ids":{"openalex":"https://openalex.org/W4386729001","doi":"https://doi.org/10.1145/3604915.3608830"},"language":"en","primary_location":{"id":"doi:10.1145/3604915.3608830","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3604915.3608830","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3604915.3608830","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3604915.3608830","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102773384","display_name":"Mostafa Rahmani","orcid":"https://orcid.org/0009-0003-0752-1132"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mostafa Rahmani","raw_affiliation_strings":["Prime, Amazon, USA"],"raw_orcid":"https://orcid.org/0009-0003-0752-1132","affiliations":[{"raw_affiliation_string":"Prime, Amazon, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048489384","display_name":"James Caverlee","orcid":"https://orcid.org/0000-0001-8350-8528"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Caverlee","raw_affiliation_strings":["Amazon, USA"],"raw_orcid":"https://orcid.org/0000-0001-8350-8528","affiliations":[{"raw_affiliation_string":"Amazon, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085428743","display_name":"Fei Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fei Wang","raw_affiliation_strings":["Amazon, USA"],"raw_orcid":"https://orcid.org/0000-0001-8265-0602","affiliations":[{"raw_affiliation_string":"Amazon, USA","institution_ids":["https://openalex.org/I1311688040"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102773384"],"corresponding_institution_ids":["https://openalex.org/I1311688040"],"apc_list":null,"apc_paid":null,"fwci":2.6905,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.91849369,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"784","last_page":"790"},"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":0.9958999752998352,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9793999791145325,"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":0.6852893829345703}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6852893829345703}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3604915.3608830","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3604915.3608830","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3604915.3608830","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM Conference on Recommender Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3604915.3608830","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3604915.3608830","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3604915.3608830","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386729001.pdf","grobid_xml":"https://content.openalex.org/works/W4386729001.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W2171279286","https://openalex.org/W2626454364","https://openalex.org/W2902040508","https://openalex.org/W2963367478","https://openalex.org/W2984100107","https://openalex.org/W2996931760","https://openalex.org/W3031331881","https://openalex.org/W3035178789","https://openalex.org/W3038719422","https://openalex.org/W3091993229","https://openalex.org/W3102619277","https://openalex.org/W3180733313","https://openalex.org/W3185773347","https://openalex.org/W3201149665","https://openalex.org/W3209048663","https://openalex.org/W4285252216","https://openalex.org/W4296591831","https://openalex.org/W4296604567","https://openalex.org/W4297971002"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W4402327032","https://openalex.org/W2382290278"],"abstract_inverted_index":{"Sequential":[0],"models":[1],"are":[2,35],"designed":[3],"to":[4],"learn":[5],"sequential":[6,33,63],"patterns":[7,34],"in":[8],"data":[9],"based":[10,97],"on":[11,104],"the":[12,22,38,60,109,115,122],"chronological":[13],"order":[14],"of":[15,24,55,62,111],"user":[16],"interactions.":[17,26],"However,":[18],"they":[19],"often":[20],"ignore":[21],"timestamps":[23],"these":[25],"Incorporating":[27],"time":[28,56,69,84,112],"is":[29],"crucial":[30],"because":[31],"many":[32],"time-dependent,":[36],"and":[37,89,99,118],"model":[39],"cannot":[40],"make":[41],"time-aware":[42],"recommendations":[43],"without":[44],"considering":[45],"time.":[46,77],"This":[47],"article":[48],"demonstrates":[49],"that":[50,108],"providing":[51],"a":[52,71,86,95,126],"rich":[53],"representation":[54,91],"can":[57],"significantly":[58,113],"improve":[59],"performance":[61],"models.":[64],"The":[65],"existing":[66],"literature":[67],"treats":[68],"as":[70,85],"one-dimensional":[72,123],"time-series":[73,88],"obtained":[74],"by":[75,125],"quantizing":[76],"In":[78],"this":[79],"study,":[80],"we":[81],"propose":[82],"treating":[83],"multi-dimensional":[87,119],"explore":[90],"learning":[92],"methods,":[93],"including":[94],"kernel":[96],"method":[98,124],"an":[100],"embedding-based":[101],"algorithm.":[102],"Experiments":[103],"multiple":[105],"datasets":[106],"show":[107],"inclusion":[110],"enhances":[114],"model\u2019s":[116],"performance,":[117],"methods":[120],"outperform":[121],"substantial":[127],"margin.":[128]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}