{"id":"https://openalex.org/W4412377151","doi":"https://doi.org/10.1145/3726302.3729940","title":"CSRec: Rethinking Sequential Recommendation from A Causal Perspective.","display_name":"CSRec: Rethinking Sequential Recommendation from A Causal Perspective.","publication_year":2025,"publication_date":"2025-07-13","ids":{"openalex":"https://openalex.org/W4412377151","doi":"https://doi.org/10.1145/3726302.3729940"},"language":"en","primary_location":{"id":"doi:10.1145/3726302.3729940","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3729940","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729940","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729940","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xiaoyu Liu","orcid":"https://orcid.org/0000-0003-3385-4726"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xiaoyu Liu","raw_affiliation_strings":["University of Maryland, College Park, College Park, MD, USA"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022328750","display_name":"Jiaxin Yuan","orcid":"https://orcid.org/0009-0007-1107-2447"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiaxin Yuan","raw_affiliation_strings":["University of Maryland, College Park, College Park, MD, USA"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101972658","display_name":"Yuhang Zhou","orcid":"https://orcid.org/0000-0003-2563-3712"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuhang Zhou","raw_affiliation_strings":["University of Maryland, College Park, College Park, MD, USA"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jingling Li","orcid":"https://orcid.org/0000-0002-5593-5466"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingling Li","raw_affiliation_strings":["University of Maryland, College Park, College Park, Maryland, USA"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, College Park, Maryland, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112044120","display_name":"Fang Huang","orcid":"https://orcid.org/0000-0001-5171-145X"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Furong Huang","raw_affiliation_strings":["University of Maryland, College Park, College Park, Maryland, USA"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, College Park, Maryland, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062903694","display_name":"Wei Ai","orcid":"https://orcid.org/0000-0001-6271-9430"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Ai","raw_affiliation_strings":["University of Maryland, College Park, College Park, MD, USA"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":9.2334,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.97605478,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1562","last_page":"1571"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9972000122070312,"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/perspective","display_name":"Perspective (graphical)","score":0.7464941740036011},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6362857818603516},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.34967780113220215},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3115352392196655}],"concepts":[{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.7464941740036011},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6362857818603516},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34967780113220215},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3115352392196655}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3726302.3729940","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3729940","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729940","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3726302.3729940","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3729940","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729940","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1523888516","display_name":null,"funder_award_id":"FA9550-","funder_id":"https://openalex.org/F4320338279","funder_display_name":"Air Force Office of Scientific Research"},{"id":"https://openalex.org/G5702281522","display_name":"FAI: Toward Fair Decision Making and Resource Allocation with Application to AI-Assisted Graduate Admission and Degree Completion","funder_award_id":"2147276","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5809100787","display_name":null,"funder_award_id":"FA9550","funder_id":"https://openalex.org/F4320338279","funder_display_name":"Air Force Office of Scientific Research"},{"id":"https://openalex.org/G5921281487","display_name":null,"funder_award_id":"number","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6509229697","display_name":null,"funder_award_id":"IIS-2147276 FAI","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7320824963","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306078","funder_display_name":"U.S. Department of Defense"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306078","display_name":"U.S. Department of Defense","ror":"https://ror.org/0447fe631"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320338279","display_name":"Air Force Office of Scientific Research","ror":"https://ror.org/011e9bt93"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412377151.pdf","grobid_xml":"https://content.openalex.org/works/W4412377151.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W2155653793","https://openalex.org/W2734755249","https://openalex.org/W2750004028","https://openalex.org/W2783272285","https://openalex.org/W2911829170","https://openalex.org/W2963367478","https://openalex.org/W2971196067","https://openalex.org/W2984100107","https://openalex.org/W3038744824","https://openalex.org/W3100521056","https://openalex.org/W3206127589","https://openalex.org/W4220974940","https://openalex.org/W4224313077","https://openalex.org/W4283205337","https://openalex.org/W4372267124","https://openalex.org/W4384648390","https://openalex.org/W4384655737","https://openalex.org/W4385270068","https://openalex.org/W4385562487","https://openalex.org/W4385713972","https://openalex.org/W4387841511","https://openalex.org/W4390490824","https://openalex.org/W4393153637","https://openalex.org/W4394589830","https://openalex.org/W4403221479"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2018871932","https://openalex.org/W2001405890"],"abstract_inverted_index":{"The":[0],"essence":[1],"of":[2,56,79,86,135],"sequential":[3,20,80,112],"recommender":[4,136,164],"systems":[5,137],"(RecSys)":[6],"lies":[7],"in":[8,29,38,45,92,157],"understanding":[9],"how":[10,48,116,151],"users":[11],"make":[12],"decisions.Most":[13],"existing":[14,175],"approaches":[15],"frame":[16],"the":[17,54,57,89,133,158,162,187],"task":[18],"as":[19],"prediction":[21],"based":[22],"on":[23,60,138,179],"users'":[24,31,61,155],"historical":[25],"purchase":[26],"records.Although":[27],"effective":[28],"capturing":[30],"natural":[32,100],"preferences,":[33],"this":[34],"formulation":[35,78],"falls":[36],"short":[37],"accurately":[39],"modeling":[40],"actual":[41,104],"recommendation":[42],"scenarios,":[43],"particularly":[44],"accounting":[46],"for":[47,145],"unsuccessful":[49],"recommendations":[50],"influence":[51,154],"future":[52],"purchases.Furthermore,":[53],"impact":[55,134],"RecSys":[58],"itself":[59],"decisions":[62,118],"has":[63],"not":[64],"been":[65],"appropriately":[66],"isolated":[67],"and":[68,102,114,121,147,160,182],"quantitatively":[69],"analyzed.To":[70],"address":[71],"these":[72],"challenges,":[73],"we":[74],"propose":[75],"a":[76,93,98,111,128],"novel":[77],"recommendation,":[81],"called":[82],"Causal":[83],"Sequential":[84],"Recommendation.Instead":[85],"merely":[87],"predicting":[88],"next":[90],"item":[91],"sequence,":[94],"CSRec":[95],"distinguishes":[96],"between":[97],"user's":[99],"preference":[101],"their":[103],"purchasing":[105],"decision.It":[106],"predicts":[107],"both":[108,180],"aspects":[109],"within":[110],"context":[113],"traces":[115],"current":[117],"are":[119],"formed":[120],"causally":[122],"influenced":[123],"by":[124],"various":[125],"factors.Applying":[126],"such":[127],"causal":[129],"framework":[130],"can":[131,170,195],"isolate":[132],"user":[139],"decisions,":[140],"thereby":[141],"opening":[142],"new":[143],"avenues":[144],"evaluation":[146],"design.This":[148],"includes":[149],"assessing":[150],"different":[152],"strategies":[153],"trust":[156],"system":[159,165],"determining":[161],"optimal":[163],"to":[166],"maximize":[167],"advertising":[168],"benefits.CSRec":[169],"be":[171,196],"seamlessly":[172],"integrated":[173],"into":[174],"next-prediction-based":[176],"methodologies.Experimental":[177],"evaluations":[178],"synthetic":[181],"real-world":[183],"datasets":[184],"demonstrate":[185],"that":[186],"proposed":[188],"implementation":[189],"significantly":[190],"improves":[191],"upon":[192],"state-of-the-art":[193],"baselines.[code":[194],"accessed":[197],"here].":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
