{"id":"https://openalex.org/W4400490596","doi":"https://doi.org/10.1109/cscwd61410.2024.10580350","title":"Causal Inference for Eliminating Popularity Bias in Session-based Recommendation","display_name":"Causal Inference for Eliminating Popularity Bias in Session-based Recommendation","publication_year":2024,"publication_date":"2024-05-08","ids":{"openalex":"https://openalex.org/W4400490596","doi":"https://doi.org/10.1109/cscwd61410.2024.10580350"},"language":"en","primary_location":{"id":"doi:10.1109/cscwd61410.2024.10580350","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/cscwd61410.2024.10580350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","raw_type":"proceedings-article"},"type":"article","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/A5100412804","display_name":"Lin Li","orcid":"https://orcid.org/0000-0001-6124-5237"},"institutions":[{"id":"https://openalex.org/I1300757298","display_name":"Heilongjiang University of Science and Technology","ror":"https://ror.org/030xwyx96","country_code":"CN","type":"education","lineage":["https://openalex.org/I1300757298"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lin Li","raw_affiliation_strings":["Heilongjiang University,School of Computer Science and Technology,Harbin,China"],"affiliations":[{"raw_affiliation_string":"Heilongjiang University,School of Computer Science and Technology,Harbin,China","institution_ids":["https://openalex.org/I1300757298"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080208129","display_name":"Jinghua Zhu","orcid":"https://orcid.org/0000-0002-5918-8453"},"institutions":[{"id":"https://openalex.org/I1300757298","display_name":"Heilongjiang University of Science and Technology","ror":"https://ror.org/030xwyx96","country_code":"CN","type":"education","lineage":["https://openalex.org/I1300757298"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinghua Zhu","raw_affiliation_strings":["Heilongjiang University,School of Computer Science and Technology,Harbin,China"],"affiliations":[{"raw_affiliation_string":"Heilongjiang University,School of Computer Science and Technology,Harbin,China","institution_ids":["https://openalex.org/I1300757298"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100412804"],"corresponding_institution_ids":["https://openalex.org/I1300757298"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19451106,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1298","last_page":"1303"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.972000002861023,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.972000002861023,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13718","display_name":"Media Influence and Politics","score":0.906499981880188,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9004999995231628,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/session","display_name":"Session (web analytics)","score":0.7823687195777893},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.7788691520690918},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7333910465240479},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6449004411697388},{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.5680500864982605},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3416970372200012},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2979692220687866},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.2471964955329895},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.19113048911094666},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.15612635016441345},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08415499329566956}],"concepts":[{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.7823687195777893},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.7788691520690918},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7333910465240479},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6449004411697388},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.5680500864982605},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3416970372200012},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2979692220687866},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.2471964955329895},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.19113048911094666},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.15612635016441345},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08415499329566956},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cscwd61410.2024.10580350","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/cscwd61410.2024.10580350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4000000059604645}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"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":{"The":[0],"general":[1],"goal":[2],"of":[3,63,109,166,181,189],"the":[4,34,55,107,134,139,150,155,158,164,170,179,186,197,202,219,230,237],"recommender":[5],"system":[6],"is":[7,80,147],"to":[8,42,52,82,87,105,132,157,192,216,222],"provide":[9],"users":[10],"with":[11,224],"precise":[12],"and":[13,45,117,142,208,233],"personalized":[14],"recommendations,":[15],"rather":[16],"than":[17],"popular":[18],"items.":[19],"However,":[20],"popularity":[21,56,65,89,111,120,145,183,225],"bias":[22,57,66,90,121,146,226],"widely":[23],"exists":[24],"in":[25,30,138],"existing":[26,48,61],"recommendation":[27,69,140,171,231],"models,":[28],"especially":[29,91],"Session-Based":[31],"Recommendation(SBR)":[32],"since":[33],"short-term":[35],"users\u2019":[36,78],"behaviors":[37],"are":[38,70,95],"much":[39],"more":[40],"susceptible":[41],"data":[43],"skew":[44],"popularity.":[46],"Unfortunately,":[47],"SBR":[49,74,94,205,239],"methods":[50,62,86],"fail":[51],"explicitly":[53],"take":[54],"into":[58,201],"consideration.":[59],"Moreover,":[60],"eliminating":[64,119],"for":[67,73,93],"sequence":[68],"not":[71],"suitable":[72],"scenarios":[75],"where":[76],"anonymous":[77],"information":[79],"hard":[81],"obtain.":[83],"Thus,":[84],"effective":[85],"eliminate":[88,178],"designed":[92],"needed.":[96],"In":[97],"this":[98],"paper,":[99],"we":[100,126,162,177],"leverage":[101],"causal":[102,115,130,136,167],"inference":[103,221],"theory":[104],"analyze":[106],"impact":[108,165,180,188],"item":[110,156,182],"by":[112,149,184],"establishing":[113],"a":[114,129],"graph":[116,131],"then":[118],"through":[122,173],"counterfactual":[123,193],"reasoning.":[124,194],"Specifically,":[125],"first":[127],"construct":[128],"describe":[133],"important":[135],"relationship":[137],"process":[141],"find":[143],"that":[144,218],"caused":[148],"direct":[151,187],"influence":[152],"path":[153],"from":[154],"ranking":[159],"score.":[160],"Then":[161],"model":[163,206,235],"relationships":[168],"on":[169,212],"score":[172],"multi-task":[174],"training.":[175],"Finally,":[176],"removing":[185],"items":[190],"according":[191],"We":[195],"integrate":[196],"proposed":[198],"popularity-eliminating":[199],"method":[200],"recently":[203],"outstanding":[204],"COTREC":[207],"conduct":[209],"extensive":[210],"experiments":[211],"two":[213],"real":[214],"datasets":[215],"validate":[217],"casual":[220],"deal":[223],"could":[227],"further":[228],"improve":[229],"accuracy":[232],"our":[234],"outperforms":[236],"SOTA":[238],"models":[240],"consistently.":[241]},"counts_by_year":[],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}