{"id":"https://openalex.org/W6929572426","doi":"https://doi.org/10.48550/arxiv.2506.17682","title":"Reinforcing User Interest Evolution in Multi-Scenario Learning for recommender systems","display_name":"Reinforcing User Interest Evolution in Multi-Scenario Learning for recommender systems","publication_year":2025,"publication_date":"2025-06-21","ids":{"openalex":"https://openalex.org/W6929572426","doi":"https://doi.org/10.48550/arxiv.2506.17682"},"language":"en","primary_location":{"id":"doi:10.48550/arxiv.2506.17682","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.17682","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2506.17682","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Feng, Zhijian","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Feng, Zhijian","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Zheng, Wenhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Wenhao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Xiao, Xuanji","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Xuanji","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10031","display_name":"T-cell and B-cell Immunology","score":0.47870001196861267,"subfield":{"id":"https://openalex.org/subfields/2403","display_name":"Immunology"},"field":{"id":"https://openalex.org/fields/24","display_name":"Immunology and Microbiology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10031","display_name":"T-cell and B-cell Immunology","score":0.47870001196861267,"subfield":{"id":"https://openalex.org/subfields/2403","display_name":"Immunology"},"field":{"id":"https://openalex.org/fields/24","display_name":"Immunology and Microbiology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T14072","display_name":"Immunotoxicology and immune responses","score":0.2500999867916107,"subfield":{"id":"https://openalex.org/subfields/2403","display_name":"Immunology"},"field":{"id":"https://openalex.org/fields/24","display_name":"Immunology and Microbiology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10371","display_name":"Immune Response and Inflammation","score":0.01940000057220459,"subfield":{"id":"https://openalex.org/subfields/2403","display_name":"Immunology"},"field":{"id":"https://openalex.org/fields/24","display_name":"Immunology and Microbiology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.7235999703407288},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6603999733924866},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.656000018119812},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.6462000012397766},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5929999947547913},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.5202000141143799}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8027999997138977},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7235999703407288},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6603999733924866},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.656000018119812},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.6462000012397766},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5929999947547913},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.5202000141143799},{"id":"https://openalex.org/C67712803","wikidata":"https://www.wikidata.org/wiki/Q7901853","display_name":"User modeling","level":3,"score":0.47769999504089355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4180000126361847},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40689998865127563},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3889999985694885},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.37459999322891235},{"id":"https://openalex.org/C2777868144","wikidata":"https://www.wikidata.org/wiki/Q7239817","display_name":"Preference elicitation","level":3,"score":0.3508000075817108},{"id":"https://openalex.org/C181204326","wikidata":"https://www.wikidata.org/wiki/Q7239820","display_name":"Preference learning","level":3,"score":0.2921999990940094},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2621000111103058},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2581999897956848},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.25519999861717224},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2506.17682","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.17682","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2506.17682","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.17682","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7199702262878418}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"real-world":[1],"recommendation":[2,17,117],"systems,":[3],"users":[4,27],"would":[5,23],"engage":[6],"in":[7,37,43,115],"variety":[8],"scenarios,":[9,39],"such":[10],"as":[11],"homepages,":[12],"search":[13],"pages,":[14],"and":[15,46,94,128],"related":[16],"pages.":[18],"Each":[19],"of":[20],"these":[21],"scenarios":[22,75],"reflect":[24],"different":[25,38],"aspects":[26],"focus":[28],"on.":[29],"However,":[30],"the":[31],"user":[32,72,78],"interests":[33],"may":[34],"be":[35],"inconsistent":[36],"due":[40],"to":[41,89,101],"differences":[42],"decision-making":[44],"processes":[45],"preference":[47],"expression.":[48],"This":[49],"variability":[50],"complicates":[51],"unified":[52],"modeling,":[53],"making":[54],"multi-scenario":[55,116,126],"learning":[56,68,97],"a":[57,65,122],"significant":[58],"challenge.":[59],"To":[60],"address":[61],"this,":[62],"we":[63],"propose":[64],"novel":[66],"reinforcement":[67],"approach":[69,111],"that":[70,109],"models":[71],"preferences":[73],"across":[74,81],"by":[76],"modeling":[77,127],"interest":[79],"evolution":[80],"multiple":[82],"scenarios.":[83],"Our":[84,119],"method":[85],"employs":[86],"Double":[87],"Q-learning":[88],"enhance":[90],"next-item":[91],"prediction":[92],"accuracy":[93],"optimizes":[95],"contrastive":[96],"loss":[98],"using":[99],"Q-value":[100],"make":[102],"model":[103],"performance":[104],"better.":[105],"Experimental":[106],"results":[107],"demonstrate":[108],"our":[110],"surpasses":[112],"state-of-the-art":[113],"methods":[114],"tasks.":[118],"work":[120],"offers":[121],"fresh":[123],"perspective":[124],"on":[125],"highlights":[129],"promising":[130],"directions":[131],"for":[132],"future":[133],"research.":[134]},"counts_by_year":[],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}
