{"id":"https://openalex.org/W4306316949","doi":"https://doi.org/10.1145/3511808.3557645","title":"Modeling Latent Autocorrelation for Session-based Recommendation","display_name":"Modeling Latent Autocorrelation for Session-based Recommendation","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306316949","doi":"https://doi.org/10.1145/3511808.3557645"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557645","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3511808.3557645","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3511808.3557645","source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3511808.3557645","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082368205","display_name":"Xianghong Xu","orcid":"https://orcid.org/0000-0003-2447-4107"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianghong Xu","raw_affiliation_strings":["Tsinghua University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062713713","display_name":"Kai Ouyang","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Ouyang","raw_affiliation_strings":["Tsinghua University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050223298","display_name":"Liuyin Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liuyin Wang","raw_affiliation_strings":["Tsinghua University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055290241","display_name":"Jiaxin Zou","orcid":"https://orcid.org/0009-0009-7870-0174"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxin Zou","raw_affiliation_strings":["Tsinghua University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111797210","display_name":"Yanxiong Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanxiong Lu","raw_affiliation_strings":["Tencent, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022672030","display_name":"Hai-Tao Zheng","orcid":"https://orcid.org/0000-0001-5128-5649"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai-Tao Zheng","raw_affiliation_strings":["Tsinghua University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058110900","display_name":"Hong\u2010Gee Kim","orcid":"https://orcid.org/0000-0002-2610-4321"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hong-Gee Kim","raw_affiliation_strings":["Seoul National University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5822,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.67800972,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"4605","last_page":"4609"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9958000183105469,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9894000291824341,"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/autocorrelation","display_name":"Autocorrelation","score":0.9065923690795898},{"id":"https://openalex.org/keywords/session","display_name":"Session (web analytics)","score":0.8325597047805786},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8218632340431213},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5502880811691284},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4973764717578888},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44395893812179565},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43326008319854736},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35212475061416626},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11675652861595154},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10808426141738892}],"concepts":[{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.9065923690795898},{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.8325597047805786},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8218632340431213},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5502880811691284},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4973764717578888},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44395893812179565},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43326008319854736},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35212475061416626},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11675652861595154},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10808426141738892},{"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/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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:10.1145/3511808.3557645","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3511808.3557645","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3511808.3557645","source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3511808.3557645","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3511808.3557645","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3511808.3557645","source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2754657687","display_name":null,"funder_award_id":"2021A1515012640","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G7965460898","display_name":null,"funder_award_id":"6201101015","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8814030770","display_name":null,"funder_award_id":"2021ZD0112905","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320316083","display_name":"Tencent","ror":"https://ror.org/00hhjss72"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320322392","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320337986","display_name":"Tsinghua Shenzhen International Graduate School","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4306316949.pdf","grobid_xml":"https://content.openalex.org/works/W4306316949.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W2110880609","https://openalex.org/W2171279286","https://openalex.org/W2626454364","https://openalex.org/W2746011824","https://openalex.org/W2795199972","https://openalex.org/W2809307135","https://openalex.org/W2899457523","https://openalex.org/W2907492528","https://openalex.org/W2951217911","https://openalex.org/W2951431594","https://openalex.org/W2955669675","https://openalex.org/W2963367478","https://openalex.org/W2963782415","https://openalex.org/W2964044287","https://openalex.org/W2964926209","https://openalex.org/W2984100107","https://openalex.org/W2986515219","https://openalex.org/W3031331881","https://openalex.org/W3034329572","https://openalex.org/W3095937012","https://openalex.org/W3101063193","https://openalex.org/W3101707147","https://openalex.org/W3102619277","https://openalex.org/W3134624922","https://openalex.org/W3165654884","https://openalex.org/W3173151551","https://openalex.org/W3173935672","https://openalex.org/W4212774754"],"related_works":["https://openalex.org/W4230197055","https://openalex.org/W4296749040","https://openalex.org/W621808327","https://openalex.org/W747394405","https://openalex.org/W644007644","https://openalex.org/W2497198634","https://openalex.org/W3012257603","https://openalex.org/W1586784764","https://openalex.org/W4292264782","https://openalex.org/W1559289099"],"abstract_inverted_index":{"Session-based":[0],"Recommendation":[1],"(SBR)":[2],"aims":[3],"to":[4,33,72,118,121,140,151],"predict":[5],"the":[6,10,29,74,95,101,106,123,142,153,183],"next":[7],"item":[8,127],"for":[9],"current":[11],"session,":[12],"which":[13],"consists":[14],"of":[15,28,76,98,108,125],"several":[16,148],"clicked":[17,126],"items":[18],"in":[19,79,100,189],"a":[20,87,109],"short":[21],"period":[22],"by":[23,94],"an":[24],"anonymous":[25],"user.":[26],"Most":[27],"sequential":[30,65],"modeling":[31],"approaches":[32],"SBR":[34,59,91],"are":[35],"focusing":[36],"on":[37,177],"adopting":[38],"advanced":[39],"Deep":[40],"Neural":[41],"Networks":[42],"(DNNs),":[43],"and":[44,89,144,167,192],"these":[45],"methods":[46,60,78],"require":[47],"increasingly":[48],"longer":[49],"training":[50],"times.":[51],"Existing":[52],"studies":[53,69],"have":[54,70],"shown":[55],"that":[56,182],"some":[57,63],"traditional":[58,77],"can":[61,162],"outperform":[62],"DNN-based":[64,173],"models,":[66],"however,":[67],"few":[68],"attempted":[71],"investigate":[73],"effectiveness":[75,191],"recent":[80],"years.":[81],"In":[82],"this":[83,157],"paper,":[84],"we":[85,134],"propose":[86],"novel":[88],"concise":[90],"model":[92,122],"inspired":[93],"basic":[96],"concept":[97],"autocorrelation":[99,143],"Stochastic":[102],"Process.":[103],"Autocorrelation":[104],"measures":[105],"correlation":[107,124],"process":[110],"at":[111,129],"different":[112,130],"moments.":[113],"Therefore,":[114],"it":[115,120,146],"is":[116,168],"natural":[117],"use":[119,135],"sequences":[128],"time":[131],"shifts.":[132],"Specifically,":[133],"Fast":[136],"Fourier":[137],"Transforms":[138],"(FFT)":[139],"compute":[141],"combine":[145],"with":[147],"linear":[149],"transformations":[150],"enhance":[152],"session":[154,165],"representation.":[155],"By":[156],"means,":[158],"our":[159],"proposed":[160,184],"method":[161,185],"learn":[163],"better":[164],"preferences":[166],"more":[169],"efficient":[170],"than":[171],"most":[172],"models.":[174],"Extensive":[175],"experiments":[176],"two":[178],"public":[179],"datasets":[180],"show":[181],"outperforms":[186],"state-of-the-art":[187],"models":[188],"both":[190],"efficiency.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}