{"id":"https://openalex.org/W7093370831","doi":"https://doi.org/10.1109/idsta66210.2025.11202848","title":"Off-Policy Evaluation and Learning of Multi-Action Recommendation Considering Unrecommended Action Rewards","display_name":"Off-Policy Evaluation and Learning of Multi-Action Recommendation Considering Unrecommended Action Rewards","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W7093370831","doi":"https://doi.org/10.1109/idsta66210.2025.11202848"},"language":null,"primary_location":{"id":"doi:10.1109/idsta66210.2025.11202848","is_oa":false,"landing_page_url":"https://doi.org/10.1109/idsta66210.2025.11202848","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Sixth International Conference on Intelligent Data Science Technologies and Applications (IDSTA)","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":null,"display_name":"Riki OKAMURA","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Riki OKAMURA","raw_affiliation_strings":["Waseda University,Dept. of Computer Science and Communications Engineering,Tokyo,Japan,1950055"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Dept. of Computer Science and Communications Engineering,Tokyo,Japan,1950055","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":null,"display_name":"Toshiharu SUGAWARA","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Toshiharu SUGAWARA","raw_affiliation_strings":["Waseda University,Dept. of Computer Science and Communications Engineering,Tokyo,Japan,1950055"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Dept. of Computer Science and Communications Engineering,Tokyo,Japan,1950055","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.57266452,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"109","last_page":"116"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.4828000068664551,"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"}},"topics":[{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.4828000068664551,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.29820001125335693,"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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.029500000178813934,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.8234000205993652},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.697700023651123},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6747999787330627},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6348999738693237},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4717000126838684},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.3912999927997589},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.38449999690055847}],"concepts":[{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.8234000205993652},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.697700023651123},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6747999787330627},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6523000001907349},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.638700008392334},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6348999738693237},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.557200014591217},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4717000126838684},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.3912999927997589},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.38449999690055847},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.3750999867916107},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.3625999987125397},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.35670000314712524},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3343000113964081},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.2734000086784363},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C2780490138","wikidata":"https://www.wikidata.org/wiki/Q7079636","display_name":"Offline learning","level":3,"score":0.25}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/idsta66210.2025.11202848","is_oa":false,"landing_page_url":"https://doi.org/10.1109/idsta66210.2025.11202848","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Sixth International Conference on Intelligent Data Science Technologies and Applications (IDSTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4537757337093353}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1968185435","https://openalex.org/W2604520541","https://openalex.org/W3001218531","https://openalex.org/W3044963235","https://openalex.org/W3088432326","https://openalex.org/W4283022819","https://openalex.org/W4382490899","https://openalex.org/W4391590817","https://openalex.org/W4396759029","https://openalex.org/W4403221787"],"related_works":[],"abstract_inverted_index":{"We":[0],"propose":[1],"two":[2],"estimators":[3,62,128],"for":[4,63,70,113],"multi-action":[5,137],"recommendations":[6],"that":[7],"consider":[8],"the":[9,35,82,87,133,153,158],"rewards":[10,122],"from":[11,26],"unrecommended":[12,120],"actions.":[13],"Off-policy":[14],"learning":[15],"(OPL)":[16],"is":[17],"a":[18,124,140],"reinforcement-learning":[19],"approach":[20],"in":[21,49,136],"which":[22],"an":[23],"agent":[24],"learns":[25],"offline":[27,108],"data":[28],"collected":[29],"by":[30],"another":[31],"agent,":[32],"thereby":[33],"improving":[34],"target":[36],"policy":[37],"without":[38,123],"direct":[39],"environmental":[40],"interactions":[41],"during":[42],"training.":[43],"This":[44],"technique":[45],"has":[46],"been":[47,68],"applied":[48],"decision-making":[50],"and":[51,58,90,102,155],"recommendation":[52,91,145],"systems":[53],"to":[54,72],"increase":[55],"predictive":[56],"accuracy":[57],"interpretability.":[59],"While":[60],"several":[61],"off-policy":[64],"evaluation":[65,109,143],"(OPE)":[66],"have":[67],"proposed":[69,95,159],"OPL":[71],"recommend":[73],"multiple":[74],"actions,":[75],"these":[76],"methods":[77],"face":[78],"exponential":[79],"expansion":[80],"of":[81,110,132,144,157],"action":[83,116,121,134],"space":[84,135],"when":[85],"considering":[86,119],"ranking":[88,125],"order":[89],"set":[92],"size.":[93],"Our":[94],"estimators,":[96],"combined":[97,103],"inverse":[98],"propensity":[99],"score":[100],"(CIPS)":[101],"doubly":[104],"robust":[105],"(CDR),":[106],"enable":[107],"decisionmaking":[111],"models":[112],"recommending":[114],"fixed-size":[115],"subsets":[117],"while":[118],"order.":[126],"These":[127],"avoid":[129],"combinatorial":[130],"explosion":[131],"recommendations,":[138],"enabling":[139],"more":[141],"effective":[142],"structures.":[146],"Experiments":[147],"conducted":[148],"under":[149],"various":[150],"conditions":[151],"demonstrated":[152],"effectiveness":[154],"applicability":[156],"method.":[160]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-24T00:00:00"}