{"id":"https://openalex.org/W4387848827","doi":"https://doi.org/10.1145/3583780.3615244","title":"SeqGen: A Sequence Generator via User Side Information for Behavior Sparsity in Recommendation","display_name":"SeqGen: A Sequence Generator via User Side Information for Behavior Sparsity in Recommendation","publication_year":2023,"publication_date":"2023-10-21","ids":{"openalex":"https://openalex.org/W4387848827","doi":"https://doi.org/10.1145/3583780.3615244"},"language":"en","primary_location":{"id":"doi:10.1145/3583780.3615244","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583780.3615244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101891282","display_name":"Min Xu","orcid":"https://orcid.org/0000-0002-5952-0794"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu Min","raw_affiliation_strings":["Ant Group, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5952-0794","affiliations":[{"raw_affiliation_string":"Ant Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100746436","display_name":"Xiaolu Zhang","orcid":"https://orcid.org/0000-0001-8055-0245"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaolu Zhang","raw_affiliation_strings":["Ant Group, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8055-0245","affiliations":[{"raw_affiliation_string":"Ant Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053959119","display_name":"Bin Shen","orcid":"https://orcid.org/0000-0002-0167-3034"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bin Shen","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-0167-3034","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021868402","display_name":"Shuhan Wang","orcid":"https://orcid.org/0009-0006-6198-7031"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuhan Wang","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0006-6198-7031","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082449442","display_name":"Yong He","orcid":"https://orcid.org/0009-0000-5390-2655"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yong He","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0000-5390-2655","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100330872","display_name":"Changsheng Li","orcid":"https://orcid.org/0000-0001-5822-3408"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changsheng Li","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5822-3408","affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045140292","display_name":"Jun Zhou","orcid":"https://orcid.org/0000-0001-6033-6102"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Zhou","raw_affiliation_strings":["Ant Group, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6033-6102","affiliations":[{"raw_affiliation_string":"Ant Group, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"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":"4205","last_page":"4209"},"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":0.992900013923645,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9451000094413757,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8430140614509583},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.8000486493110657},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5735487341880798},{"id":"https://openalex.org/keywords/movielens","display_name":"MovieLens","score":0.5601240992546082},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5591205358505249},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5105239152908325},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4732136130332947},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4515300989151001},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.4397454857826233},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.4265609383583069},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42385274171829224},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3919960856437683},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.2007092535495758}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8430140614509583},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.8000486493110657},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5735487341880798},{"id":"https://openalex.org/C2776156558","wikidata":"https://www.wikidata.org/wiki/Q4353746","display_name":"MovieLens","level":4,"score":0.5601240992546082},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5591205358505249},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5105239152908325},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4732136130332947},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4515300989151001},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.4397454857826233},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.4265609383583069},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42385274171829224},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3919960856437683},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.2007092535495758},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"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/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3583780.3615244","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583780.3615244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5899999737739563}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2219888463","https://openalex.org/W2512971201","https://openalex.org/W2723293840","https://openalex.org/W2783272285","https://openalex.org/W2905461678","https://openalex.org/W2962745591","https://openalex.org/W2963367478","https://openalex.org/W2982902390","https://openalex.org/W2984100107","https://openalex.org/W3153754021","https://openalex.org/W3158237717","https://openalex.org/W4220974940"],"related_works":["https://openalex.org/W2524663498","https://openalex.org/W2113380565","https://openalex.org/W2781850661","https://openalex.org/W3004286290","https://openalex.org/W4233347881","https://openalex.org/W2169020911","https://openalex.org/W4242809128","https://openalex.org/W2297964623","https://openalex.org/W2907069037","https://openalex.org/W1518338130"],"abstract_inverted_index":{"In":[0,93],"real-world":[1],"industrial":[2],"advertising":[3,231],"systems,":[4],"user":[5,55,102,144,184,190],"behavior":[6,106,117,145,191],"sparsity":[7,192],"is":[8,68],"a":[9,35,46,69,97,249],"key":[10],"issue":[11,142],"that":[12,19],"affects":[13],"online":[14],"recommendation":[15,27],"performance.":[16],"We":[17,194],"observe":[18],"users":[20,114,128],"with":[21,31,115,129,165],"rich":[22,63,124],"behaviors":[23,33,131],"can":[24,75,122],"obtain":[25],"better":[26],"results":[28],"than":[29],"those":[30],"sparse":[32,65,130],"in":[34,50,90,216,228,253],"conversion-rate":[36],"(CVR)":[37],"prediction":[38],"model.":[39],"Inspired":[40],"by":[41,245],"this":[42],"phenomenon,":[43],"we":[44,224],"propose":[45],"new":[47],"method":[48,208],"SeqGen,":[49],"an":[51,160,210],"effort":[52],"to":[53,58,139,182,214],"exploit":[54,183],"side":[56,103,135,185],"information":[57,104,186],"bridge":[59],"the":[60,101,110,113,141,156,166,171,179,189,196,201,219,229,238,242,256],"gap":[61],"between":[62,100],"and":[64,71,83,105,206,247],"behaviors.":[66],"SeqGen":[67,95,121,199,227],"learnable":[70],"pluggable":[72],"module,":[73],"which":[74,236],"be":[76,153],"easily":[77],"integrated":[78],"into":[79,155],"any":[80],"CVR":[81,162,243],"model":[82,163,244],"no":[84],"longer":[85],"requires":[86],"two-stage":[87],"training":[88],"as":[89,138],"previous":[91],"works.":[92],"particular,":[94],"learns":[96],"mapping":[98],"relationship":[99],"sequences,":[107],"only":[108],"on":[109,133,200,259],"basis":[111],"of":[112,143,159,173,198,212,218,234,241,251,255],"long":[116],"sequences.":[118],"After":[119],"that,":[120],"generate":[123],"sequence":[125,149,168],"features":[126,150],"for":[127,187],"based":[132],"their":[134],"information,":[136],"so":[137],"alleviate":[140],"sparsity.":[146],"The":[147],"generated":[148],"will":[151],"then":[152],"fed":[154],"classifier":[157],"tower":[158],"arbitrary":[161],"together":[164],"original":[167],"features.":[169],"To":[170],"best":[172],"our":[174,176,207],"knowledge,":[175],"approach":[177],"constitutes":[178],"first":[180],"attempt":[181],"addressing":[188],"issue.":[193],"validate":[195],"effectiveness":[197],"publicly":[202],"available":[203],"dataset":[204],"MovieLens-1M,":[205],"receives":[209],"improvement":[211],"up":[213],"0.5%":[215],"terms":[217,254],"AUC":[220,240],"score.":[221],"More":[222],"importantly,":[223],"successfully":[225],"deploy":[226],"commercial":[230],"system":[232],"Xlight":[233],"Alipay,":[235],"improves":[237],"grouped":[239],"0.6%":[246],"brings":[248],"boost":[250],"0.49%":[252],"conversion":[257],"rate":[258],"A/B":[260],"testing.":[261]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}