{"id":"https://openalex.org/W3065542300","doi":"https://doi.org/10.1145/3340531.3411954","title":"S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization","display_name":"S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization","publication_year":2020,"publication_date":"2020-10-19","ids":{"openalex":"https://openalex.org/W3065542300","doi":"https://doi.org/10.1145/3340531.3411954","mag":"3065542300"},"language":"en","primary_location":{"id":"doi:10.1145/3340531.3411954","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3411954","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2008.07873","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Kun Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kun Zhou","raw_affiliation_strings":["Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hui Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Wang","raw_affiliation_strings":["Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wayne Xin Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wayne Xin Zhao","raw_affiliation_strings":["Renmin University of China &amp; Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China &amp; Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yutao Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I70931966","display_name":"Universit\u00e9 de Montr\u00e9al","ror":"https://ror.org/0161xgx34","country_code":"CA","type":"education","lineage":["https://openalex.org/I70931966"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yutao Zhu","raw_affiliation_strings":["Universit\u00e9 de Montr\u00e9al, Montr\u00e9al, PQ, Canada"],"affiliations":[{"raw_affiliation_string":"Universit\u00e9 de Montr\u00e9al, Montr\u00e9al, PQ, Canada","institution_ids":["https://openalex.org/I70931966"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Sirui Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sirui Wang","raw_affiliation_strings":["Meituan-Dianping Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan-Dianping Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Fuzheng Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fuzheng Zhang","raw_affiliation_strings":["Meituan-Dianping Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan-Dianping Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhongyuan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhongyuan Wang","raw_affiliation_strings":["Meituan-Dianping Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan-Dianping Group, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Ji-Rong Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji-Rong Wen","raw_affiliation_strings":["Renmin University of China &amp; Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China &amp; Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":79.0061,"has_fulltext":false,"cited_by_count":687,"citation_normalized_percentile":{"value":0.99947976,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1893","last_page":"1902"},"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":0.9879000186920166,"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":0.9822999835014343,"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/context","display_name":"Context (archaeology)","score":0.6251999735832214},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.49729999899864197},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.49480000138282776},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44040000438690186},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.40299999713897705},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.38749998807907104},{"id":"https://openalex.org/keywords/context-model","display_name":"Context model","score":0.37700000405311584},{"id":"https://openalex.org/keywords/information-loss","display_name":"Information loss","score":0.3325999975204468}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7512999773025513},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6251999735832214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5996000170707703},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.49729999899864197},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.49480000138282776},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46869999170303345},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44040000438690186},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.421099990606308},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.40299999713897705},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.38749998807907104},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.37700000405311584},{"id":"https://openalex.org/C2988416141","wikidata":"https://www.wikidata.org/wiki/Q6031139","display_name":"Information loss","level":2,"score":0.3325999975204468},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.3249000012874603},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.3215999901294708},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.2930000126361847},{"id":"https://openalex.org/C2983325608","wikidata":"https://www.wikidata.org/wiki/Q17084606","display_name":"Data association","level":3,"score":0.2924000024795532},{"id":"https://openalex.org/C113336015","wikidata":"https://www.wikidata.org/wiki/Q574010","display_name":"Complete information","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.2632000148296356}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3340531.3411954","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3411954","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2008.07873","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.07873","pdf_url":"https://arxiv.org/pdf/2008.07873","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:2008.07873","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.07873","pdf_url":"https://arxiv.org/pdf/2008.07873","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":8,"referenced_works":["https://openalex.org/W2122925692","https://openalex.org/W2138204974","https://openalex.org/W2512965516","https://openalex.org/W2625746539","https://openalex.org/W2783272285","https://openalex.org/W2892821876","https://openalex.org/W2963669159","https://openalex.org/W2970354142"],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"significant":[1],"progress":[2],"has":[3,62],"been":[4,64],"made":[5],"in":[6],"sequential":[7,14,70],"recommendation":[8,15],"with":[9,35],"deep":[10],"learning.":[11],"Existing":[12],"neural":[13],"models":[16],"usually":[17],"rely":[18],"on":[19],"the":[20,32,49,52],"item":[21],"prediction":[22],"loss":[23,37],"to":[24,40],"learn":[25],"model":[26,33],"parameters":[27],"or":[28,54],"data":[29,43,58,61],"representations.":[30],"However,":[31],"trained":[34],"this":[36],"is":[38],"prone":[39],"suffer":[41],"from":[42],"sparsity":[44],"problem.":[45],"Since":[46],"it":[47],"overemphasizes":[48],"final":[50],"performance,":[51],"association":[53],"fusion":[55],"between":[56],"context":[57],"and":[59,67],"sequence":[60],"not":[63],"well":[65],"captured":[66],"utilized":[68],"for":[69],"recommendation.":[71]},"counts_by_year":[{"year":2026,"cited_by_count":34},{"year":2025,"cited_by_count":187},{"year":2024,"cited_by_count":182},{"year":2023,"cited_by_count":165},{"year":2022,"cited_by_count":91},{"year":2021,"cited_by_count":28}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2020-08-24T00:00:00"}
