{"id":"https://openalex.org/W4388777042","doi":"https://doi.org/10.1145/3625403.3625418","title":"Contrastive Learning based Item Representation with Asymmetric Augmentation for Sequential Recommendation","display_name":"Contrastive Learning based Item Representation with Asymmetric Augmentation for Sequential Recommendation","publication_year":2023,"publication_date":"2023-09-15","ids":{"openalex":"https://openalex.org/W4388777042","doi":"https://doi.org/10.1145/3625403.3625418"},"language":"en","primary_location":{"id":"doi:10.1145/3625403.3625418","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3625403.3625418","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3625403.3625418","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 2nd International Conference on Algorithms, Data Mining, and Information Technology","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/10.1145/3625403.3625418","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086853173","display_name":"K.W. Zeng","orcid":"https://orcid.org/0009-0006-0451-7922"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kexiang Zeng","raw_affiliation_strings":["Department of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Singapore"],"raw_orcid":"https://orcid.org/0009-0006-0451-7922","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Singapore","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100662669","display_name":"Xiaoyu Shi","orcid":"https://orcid.org/0000-0002-4267-7795"},"institutions":[{"id":"https://openalex.org/I4210123021","display_name":"Chongqing Institute of Green and Intelligent Technology","ror":"https://ror.org/031npqv35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210123021"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Shi","raw_affiliation_strings":["Chongqing Key Laboratory of Big Data and IntelligentComputing, Chongqing Institute of Green and Intelligent Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-4267-7795","affiliations":[{"raw_affiliation_string":"Chongqing Key Laboratory of Big Data and IntelligentComputing, Chongqing Institute of Green and Intelligent Technology, China","institution_ids":["https://openalex.org/I4210123021"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064190343","display_name":"Hong Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123021","display_name":"Chongqing Institute of Green and Intelligent Technology","ror":"https://ror.org/031npqv35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210123021"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Xie","raw_affiliation_strings":["Chongqing Key Laboratory of Big Data and IntelligentComputing, Chongqing Institute of Green and Intelligent Technology, China"],"raw_orcid":"https://orcid.org/0000-0001-7935-7210","affiliations":[{"raw_affiliation_string":"Chongqing Key Laboratory of Big Data and IntelligentComputing, Chongqing Institute of Green and Intelligent Technology, China","institution_ids":["https://openalex.org/I4210123021"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091667639","display_name":"Mingsheng Shang","orcid":"https://orcid.org/0000-0002-7024-2270"},"institutions":[{"id":"https://openalex.org/I4210123021","display_name":"Chongqing Institute of Green and Intelligent Technology","ror":"https://ror.org/031npqv35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210123021"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingsheng Shang","raw_affiliation_strings":["Chongqing Key Laboratory of Big Data and IntelligentComputing, Chongqing Institute of Green and Intelligent Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-7024-2270","affiliations":[{"raw_affiliation_string":"Chongqing Key Laboratory of Big Data and IntelligentComputing, Chongqing Institute of Green and Intelligent Technology, China","institution_ids":["https://openalex.org/I4210123021"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5086853173"],"corresponding_institution_ids":["https://openalex.org/I10535382"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26488779,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"68","last_page":"73"},"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9876000285148621,"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":0.9807000160217285,"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":0.7796630859375},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7176113724708557},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.598824143409729},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5666148662567139},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.5530277490615845},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5216934084892273},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.519293487071991},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5113298296928406},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.49982500076293945},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4426341652870178},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4228225350379944},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.1120288074016571},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.06624853610992432}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7796630859375},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7176113724708557},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.598824143409729},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5666148662567139},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.5530277490615845},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5216934084892273},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.519293487071991},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5113298296928406},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.49982500076293945},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4426341652870178},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4228225350379944},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.1120288074016571},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.06624853610992432},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3625403.3625418","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3625403.3625418","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3625403.3625418","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 2nd International Conference on Algorithms, Data Mining, and Information Technology","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3625403.3625418","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3625403.3625418","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3625403.3625418","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 2nd International Conference on Algorithms, Data Mining, and Information Technology","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4764049442","display_name":null,"funder_award_id":"HZ2021017","funder_id":"https://openalex.org/F4320324805","funder_display_name":"Chongqing Municipal Education Commission"},{"id":"https://openalex.org/G4807448308","display_name":null,"funder_award_id":"HZ2021008","funder_id":"https://openalex.org/F4320324805","funder_display_name":"Chongqing Municipal Education Commission"},{"id":"https://openalex.org/G6007557446","display_name":null,"funder_award_id":"62072429","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"},{"id":"https://openalex.org/G7293336042","display_name":null,"funder_award_id":"62072429","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"},{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"},{"id":"https://openalex.org/F4320324805","display_name":"Chongqing Municipal Education Commission","ror":"https://ror.org/031nm5713"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388777042.pdf","grobid_xml":"https://content.openalex.org/works/W4388777042.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W2027731328","https://openalex.org/W2783272285","https://openalex.org/W2963351448","https://openalex.org/W2963367478","https://openalex.org/W2966483207","https://openalex.org/W2984100107","https://openalex.org/W2986515219","https://openalex.org/W3038719422","https://openalex.org/W3065542300","https://openalex.org/W3080374445","https://openalex.org/W3081170586","https://openalex.org/W3100260481","https://openalex.org/W3133849783","https://openalex.org/W3155496675","https://openalex.org/W3171249018","https://openalex.org/W3180733313","https://openalex.org/W4224316819","https://openalex.org/W4225791184"],"related_works":["https://openalex.org/W2368605798","https://openalex.org/W2518037665","https://openalex.org/W2348524959","https://openalex.org/W2477036161","https://openalex.org/W2368049389","https://openalex.org/W2384861574","https://openalex.org/W4294565801","https://openalex.org/W2170801710","https://openalex.org/W2952704802","https://openalex.org/W2741781807"],"abstract_inverted_index":{"Contrastive":[0,104],"learning":[1,16,86,105,122,179],"has":[2],"been":[3],"widely":[4],"applied":[5],"in":[6,59,71,79,93],"sequential":[7],"recommendation":[8,12],"to":[9,29,83,124,136,176,192],"improve":[10],"the":[11,21,31,42,63,126,133,138,194,198,201,219],"performance.":[13],"Existing":[14],"contrastive":[15,60,72,85,121,173,178],"methods":[17],"focus":[18],"on":[19,200,208],"adjusting":[20],"views":[22,152,161],"number":[23],"of":[24,65],"positive":[25],"and":[26,89,144,156,189,204],"negative":[27],"samples":[28],"enhance":[30,125],"item":[32,95,107,127,140],"representation":[33,108],"via":[34],"data-level":[35],"augmentation(e.g.,":[36],"MMInfoRec).":[37],"However,":[38],"they":[39],"generally":[40],"ignore":[41],"sampled":[43],"items":[44,54,67,191],"still":[45],"follow":[46],"a":[47,51,56,69,75,103],"long-tail":[48],"distribution,":[49],"i.e.,":[50],"few":[52],"popular":[53,88,143,154,188],"have":[55,68],"high-frequency":[57],"occurrence":[58],"learning,":[61],"while":[62],"majority":[64],"unpopular":[66,90,145,163,190],"low-frequency":[70],"learning.":[73],"As":[74],"result,":[76],"this":[77,98],"imbalance":[78],"sample":[80],"extraction":[81],"leads":[82],"insufficient":[84],"between":[87,187],"items,":[91,146,155],"resulting":[92],"sub-optimal":[94],"representation.":[96,128],"In":[97],"paper,":[99],"we":[100,130,148,166,196],"propose":[101],"CA4Rec,":[102],"based":[106],"with":[109],"Asymmetric":[110],"augmentation":[111],"for":[112,153,162],"Sequential":[113],"Recommendation,":[114],"that":[115,216],"adopts":[116],"an":[117],"asymmetric":[118,170],"augmented":[119,151,160],"multi-instance":[120,171],"strategy":[123],"Specifically,":[129],"first":[131],"use":[132,167],"popularity-aware":[134],"method":[135],"divide":[137],"entire":[139],"set":[141],"into":[142],"then":[147],"generate":[149],"k":[150,157],"+":[158],"n":[159],"items.":[164],"Finally,":[165],"our":[168],"proposed":[169],"noise":[172],"estimation":[174],"(AMINCE)":[175],"perform":[177],"calculation.":[180],"Make":[181],"sure":[182],"there":[183],"is":[184],"sufficient":[185],"contrast":[186],"mitigate":[193],"issue.":[195],"implement":[197],"improvements":[199],"state-of-the-art":[202,220],"model":[203],"conduct":[205],"extensive":[206],"experiments":[207],"three":[209],"benchmark":[210],"datasets.":[211],"The":[212],"experimental":[213],"results":[214],"demonstrate":[215],"CA4Rec":[217],"outperforms":[218],"baselines.":[221]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}