{"id":"https://openalex.org/W7131386595","doi":"https://doi.org/10.1109/icdm65498.2025.00014","title":"Invariant and Environment-specific Preference Learning with Auxiliary Information for Unbiased Recommendation","display_name":"Invariant and Environment-specific Preference Learning with Auxiliary Information for Unbiased Recommendation","publication_year":2025,"publication_date":"2025-11-12","ids":{"openalex":"https://openalex.org/W7131386595","doi":"https://doi.org/10.1109/icdm65498.2025.00014"},"language":null,"primary_location":{"id":"doi:10.1109/icdm65498.2025.00014","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm65498.2025.00014","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Data Mining (ICDM)","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/A5126777937","display_name":"Ting Bi","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Bi","raw_affiliation_strings":["Software College, Jilin University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Software College, Jilin University","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014335948","display_name":"X. Xu","orcid":"https://orcid.org/0000-0002-8148-3539"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hangtong XU","raw_affiliation_strings":["College of Computer Science and Technology, Jilin University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Jilin University","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101136194","display_name":"Yuanbo Xu","orcid":"https://orcid.org/0000-0002-2051-3968"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanbo Xu","raw_affiliation_strings":["Software College, Jilin University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Software College, Jilin University","institution_ids":["https://openalex.org/I194450716"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I194450716"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.70793079,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"71","last_page":"80"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.7088000178337097,"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":0.7088000178337097,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.0478999987244606,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.03139999881386757,"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/recommender-system","display_name":"Recommender system","score":0.6371999979019165},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.5791000127792358},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5641999840736389},{"id":"https://openalex.org/keywords/preference-learning","display_name":"Preference learning","score":0.36059999465942383},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.2709999978542328}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7459999918937683},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6371999979019165},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.5791000127792358},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5641999840736389},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5224999785423279},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48890000581741333},{"id":"https://openalex.org/C181204326","wikidata":"https://www.wikidata.org/wiki/Q7239820","display_name":"Preference learning","level":3,"score":0.36059999465942383},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30649998784065247},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C2780148112","wikidata":"https://www.wikidata.org/wiki/Q1432581","display_name":"Proxy (statistics)","level":2,"score":0.26919999718666077},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2612000107765198},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2574999928474426},{"id":"https://openalex.org/C67712803","wikidata":"https://www.wikidata.org/wiki/Q7901853","display_name":"User modeling","level":3,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdm65498.2025.00014","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm65498.2025.00014","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Data Mining (ICDM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6088238954544067,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1886704267","https://openalex.org/W2101409192","https://openalex.org/W2748058847","https://openalex.org/W2892888989","https://openalex.org/W3034348890","https://openalex.org/W3035404611","https://openalex.org/W3088936686","https://openalex.org/W3097679710","https://openalex.org/W3121192132","https://openalex.org/W4220806694","https://openalex.org/W4290944323","https://openalex.org/W4320830010","https://openalex.org/W4385767887","https://openalex.org/W4389076429","https://openalex.org/W4396757563","https://openalex.org/W4400925671","https://openalex.org/W4406264066","https://openalex.org/W4409667646"],"related_works":[],"abstract_inverted_index":{"Invariant":[0,93],"user":[1,13,27,80,127],"preference":[2,128,141],"learning":[3,57,121],"is":[4,15],"a":[5,90,106],"core":[6],"task":[7],"in":[8,29,114],"recommender":[9],"systems.":[10],"Accurately":[11],"modeling":[12,191],"preferences":[14,28,39,59,81,164],"crucial,":[16],"as":[17,105],"it":[18],"directly":[19],"impacts":[20],"the":[21,76,111,116,120],"quality":[22],"of":[23,79,122],"recommendations.":[24,168],"However,":[25],"heterogeneous":[26],"feedback":[30,51],"data":[31,52],"often":[32,65],"exhibit":[33],"mixture":[34],"distributions,":[35],"which":[36],"obscure":[37],"invariant":[38,58,161],"and":[40,56,72,94,125,159,162],"introduce":[41],"bias.":[42],"Existing":[43],"methods":[44],"typically":[45],"address":[46],"this":[47],"issue":[48],"by":[49],"partitioning":[50,115],"into":[53],"multiple":[54],"environments":[55],"across":[60,82],"them.":[61],"Nonetheless,":[62],"these":[63,86],"approaches":[64],"lack":[66],"theoretical":[67,130],"guarantees":[68],"for":[69,97,167],"environment":[70,112,148],"construction":[71],"fail":[73],"to":[74,109,138,144,154],"capture":[75,139],"dynamic":[77],"nature":[78],"different":[83],"environments.":[84],"Along":[85],"lines,":[87],"we":[88,133],"propose":[89],"novel":[91],"framework,":[92],"Environment-specific":[95],"Preferences":[96],"unbiased":[98],"recommendation":[99,186],"(IEPref).":[100],"IEPref":[101,177],"leverages":[102],"auxiliary":[103],"information":[104],"reliable":[107],"signal":[108],"guide":[110],"classifier":[113,149],"environment,":[117,158],"thereby":[118],"enabling":[119],"more":[123],"stable":[124],"generalizable":[126],"with":[129],"guarantees.":[131],"Additionally,":[132],"design":[134],"environment-specific":[135,163],"proxy":[136],"modules":[137],"context-dependent":[140],"patterns":[142],"unique":[143],"each":[145,151],"environment.":[146],"The":[147],"assigns":[150],"user-item":[152],"interaction":[153],"its":[155],"corresponding":[156],"latent":[157],"both":[160],"are":[165],"integrated":[166],"Extensive":[169],"experiments":[170],"on":[171],"five":[172],"real-world":[173],"datasets":[174],"demonstrate":[175],"that":[176],"achieves":[178],"superior":[179],"performance":[180],"over":[181],"existing":[182],"baselines,":[183],"effectively":[184],"mitigating":[185],"bias":[187],"while":[188],"preserving":[189],"personalized":[190],"capabilities.":[192]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-02-26T00:00:00"}
