{"id":"https://openalex.org/W4376851154","doi":"https://doi.org/10.1109/tmm.2023.3276505","title":"Knowledge-Enhanced Causal Reinforcement Learning Model for Interactive Recommendation","display_name":"Knowledge-Enhanced Causal Reinforcement Learning Model for Interactive Recommendation","publication_year":2023,"publication_date":"2023-05-16","ids":{"openalex":"https://openalex.org/W4376851154","doi":"https://doi.org/10.1109/tmm.2023.3276505"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2023.3276505","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2023.3276505","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-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/A5001185571","display_name":"Weizhi Nie","orcid":"https://orcid.org/0000-0002-0578-8138"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weizhi Nie","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012702826","display_name":"Xin Wen","orcid":"https://orcid.org/0000-0001-8379-4149"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Wen","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100375136","display_name":"Jing Liu","orcid":"https://orcid.org/0000-0003-4690-1886"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Liu","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100362815","display_name":"Jiawei Chen","orcid":"https://orcid.org/0000-0002-4752-2629"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiawei Chen","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075695432","display_name":"Jiancan Wu","orcid":"https://orcid.org/0000-0002-6941-5218"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiancan Wu","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101593091","display_name":"Guoqing Jin","orcid":"https://orcid.org/0009-0001-7108-9159"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guoqing Jin","raw_affiliation_strings":["State Key Laboratory of Communication Content Cognition, People&#x0027;s Daily Online, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Communication Content Cognition, People&#x0027;s Daily Online, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100460378","display_name":"Jing L\u00fc","orcid":"https://orcid.org/0000-0001-9163-8795"},"institutions":[{"id":"https://openalex.org/I4401726859","display_name":"Kuaishou (China)","ror":"https://ror.org/0258as409","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Lu","raw_affiliation_strings":["Kuaishou Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Kuaishou Technology, Beijing, China","institution_ids":["https://openalex.org/I4401726859"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109735832","display_name":"An-An Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"An-An Liu","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China","Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5001185571"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":11.2811,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.98401211,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"26","issue":null,"first_page":"1129","last_page":"1142"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9983999729156494,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9937000274658203,"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/computer-science","display_name":"Computer science","score":0.8517618179321289},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6586645245552063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49329036474227905},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43132710456848145},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3569304943084717}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8517618179321289},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6586645245552063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49329036474227905},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43132710456848145},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3569304943084717}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2023.3276505","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2023.3276505","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7659021256","display_name":null,"funder_award_id":"62101325","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W1994389483","https://openalex.org/W2009979684","https://openalex.org/W2017710739","https://openalex.org/W2080770071","https://openalex.org/W2091780923","https://openalex.org/W2112420033","https://openalex.org/W2119717200","https://openalex.org/W2132917208","https://openalex.org/W2138108551","https://openalex.org/W2143891888","https://openalex.org/W2184957013","https://openalex.org/W2219888463","https://openalex.org/W2250342289","https://openalex.org/W2604662567","https://openalex.org/W2604822632","https://openalex.org/W2736601468","https://openalex.org/W2743159750","https://openalex.org/W2782866613","https://openalex.org/W2787933113","https://openalex.org/W2792839191","https://openalex.org/W2799544270","https://openalex.org/W2902572901","https://openalex.org/W2913560138","https://openalex.org/W2946420264","https://openalex.org/W2962872206","https://openalex.org/W2962992837","https://openalex.org/W2963619374","https://openalex.org/W2966349618","https://openalex.org/W3009802958","https://openalex.org/W3017289192","https://openalex.org/W3034791416","https://openalex.org/W3034833075","https://openalex.org/W3047443212","https://openalex.org/W3098087397","https://openalex.org/W3102899483","https://openalex.org/W3106439716","https://openalex.org/W3122193054","https://openalex.org/W3146823280","https://openalex.org/W3155850838","https://openalex.org/W3156939347","https://openalex.org/W3160537436","https://openalex.org/W3194194466","https://openalex.org/W3201455680","https://openalex.org/W3212660220","https://openalex.org/W4200633747","https://openalex.org/W4205306435","https://openalex.org/W4205430897","https://openalex.org/W4220907840","https://openalex.org/W4224313077","https://openalex.org/W4283806310","https://openalex.org/W4292423901","https://openalex.org/W4298857966","https://openalex.org/W4312583258","https://openalex.org/W4367319708","https://openalex.org/W4385245566","https://openalex.org/W4394672593","https://openalex.org/W6627932998","https://openalex.org/W6630221451","https://openalex.org/W6631190155","https://openalex.org/W6637967152","https://openalex.org/W6678830454","https://openalex.org/W6683195989","https://openalex.org/W6692935382","https://openalex.org/W6695055480","https://openalex.org/W6741002519","https://openalex.org/W6759896672","https://openalex.org/W6769700555","https://openalex.org/W6864350279"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Owing":[0],"to":[1,17,40,64,74,99,119,150],"its":[2],"inherently":[3],"dynamic":[4],"nature":[5],"and":[6,85],"economical":[7],"training":[8],"cost,":[9],"offline":[10,28,76],"reinforcement":[11,60],"learning":[12,61],"(RL)":[13],"is":[14,31,38,161],"typically":[15],"employed":[16],"implement":[18],"an":[19],"interactive":[20],"recommender":[21],"system":[22],"(IRS).":[23],"A":[24],"crucial":[25],"challenge":[26],"in":[27,68,79],"RL-based":[29],"IRSs":[30],"the":[32,46,75,82,113,132,137,141,181],"data":[33,66],"sparsity":[34,67],"issue,":[35],"i.e.,":[36],"it":[37],"hard":[39],"mine":[41],"user":[42,96,101,123,153],"preferences":[43],"well":[44],"from":[45,126],"limited":[47],"number":[48],"of":[49,81],"user-item":[50,166],"interactions.":[51],"In":[52],"this":[53],"article,":[54],"we":[55,89,130],"propose":[56,91,144],"a":[57,92,145,164],"knowledge-enhanced":[58,146],"causal":[59,95,117],"model":[62,97,178],"(KCRL)":[63],"mitigate":[65],"IRSs.":[69],"We":[70,106,143],"make":[71],"technical":[72],"extensions":[73],"RL":[77,133],"framework":[78],"terms":[80],"reward":[83,138],"function":[84],"state":[86,147,154],"representation.":[87],"Specifically,":[88],"first":[90],"group":[93,109,114],"preference-injected":[94],"(GCUM)":[98],"learn":[100,131],"satisfaction":[102],"(i.e.,":[103],"reward)":[104],"estimation.":[105],"introduce":[107],"beneficial":[108],"preference":[110],"information,":[111],"namely,":[112],"effect,":[115],"via":[116],"inference":[118],"compensate":[120],"for":[121],"incomplete":[122],"interests":[124],"extracted":[125],"sparse":[127],"data.":[128],"Then,":[129],"recommendation":[134],"policy":[135],"with":[136],"given":[139],"by":[140,163],"GCUM.":[142],"encoder":[148],"(KSE)":[149],"generate":[151],"knowledge-enriched":[152],"representations":[155],"at":[156],"each":[157],"time":[158],"step,":[159],"which":[160],"assisted":[162],"self-constructed":[165],"knowledge":[167],"graph.":[168],"Extensive":[169],"experimental":[170],"results":[171],"on":[172],"real-world":[173],"datasets":[174],"demonstrate":[175],"that":[176],"our":[177],"significantly":[179],"outperforms":[180],"baselines.":[182]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2025-10-10T00:00:00"}
