{"id":"https://openalex.org/W4416017446","doi":"https://doi.org/10.1145/3746252.3761395","title":"Target Item-oriented Conditional Diffusion Differential Transformer for Next-Item Prediction","display_name":"Target Item-oriented Conditional Diffusion Differential Transformer for Next-Item Prediction","publication_year":2025,"publication_date":"2025-11-08","ids":{"openalex":"https://openalex.org/W4416017446","doi":"https://doi.org/10.1145/3746252.3761395"},"language":null,"primary_location":{"id":"doi:10.1145/3746252.3761395","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746252.3761395","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-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":null,"display_name":"Xiaoqing Chen","orcid":"https://orcid.org/0000-0001-7288-7374"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoqing Chen","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011992844","display_name":"Zitao Xu","orcid":"https://orcid.org/0009-0009-4922-2011"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zitao Xu","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073490832","display_name":"Weike Pan","orcid":"https://orcid.org/0000-0001-6326-9531"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weike Pan","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100633979","display_name":"Zhong Ming","orcid":"https://orcid.org/0000-0002-6933-5760"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Ming","raw_affiliation_strings":["Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.46333128,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"342","last_page":"352"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9427000284194946,"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":0.9427000284194946,"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":0.011800000444054604,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.004100000020116568,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/inference","display_name":"Inference","score":0.6122999787330627},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.4122999906539917},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.3993000090122223},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.36329999566078186},{"id":"https://openalex.org/keywords/profiling","display_name":"Profiling (computer programming)","score":0.3479999899864197},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.3343000113964081},{"id":"https://openalex.org/keywords/sampling-distribution","display_name":"Sampling distribution","score":0.3147999942302704},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.3000999987125397}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.707099974155426},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6122999787330627},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5002999901771545},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4122999906539917},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3993000090122223},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37869998812675476},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3779999911785126},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.36329999566078186},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3560999929904938},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.3479999899864197},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.3343000113964081},{"id":"https://openalex.org/C167723999","wikidata":"https://www.wikidata.org/wiki/Q3773214","display_name":"Sampling distribution","level":2,"score":0.3147999942302704},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C61423126","wikidata":"https://www.wikidata.org/wiki/Q187432","display_name":"Scripting language","level":2,"score":0.29580000042915344},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2930000126361847},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.2808000147342682},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.28049999475479126},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.2587999999523163},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.2587999999523163},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C51955184","wikidata":"https://www.wikidata.org/wiki/Q1545585","display_name":"Stochastic differential equation","level":2,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746252.3761395","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746252.3761395","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5826691500","display_name":null,"funder_award_id":"62461160311, 62272315","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2074290495","https://openalex.org/W2171279286","https://openalex.org/W2171960770","https://openalex.org/W2475334473","https://openalex.org/W2604662567","https://openalex.org/W2605350416","https://openalex.org/W2783118243","https://openalex.org/W2809112621","https://openalex.org/W2963367478","https://openalex.org/W2984100107","https://openalex.org/W2997329666","https://openalex.org/W3012705926","https://openalex.org/W3035588407","https://openalex.org/W3065542300","https://openalex.org/W3185773347","https://openalex.org/W3207257408","https://openalex.org/W4224952158","https://openalex.org/W4284668205","https://openalex.org/W4285252216","https://openalex.org/W4285428788","https://openalex.org/W4306317325","https://openalex.org/W4382239673","https://openalex.org/W4387846486","https://openalex.org/W4388187265","https://openalex.org/W4393147800","https://openalex.org/W4394717656","https://openalex.org/W4394819711","https://openalex.org/W4395075604","https://openalex.org/W4399693548","https://openalex.org/W4400910497","https://openalex.org/W4403220171","https://openalex.org/W4403791004","https://openalex.org/W4403844088","https://openalex.org/W4407953541","https://openalex.org/W4409657321"],"related_works":[],"abstract_inverted_index":{"Sequential":[0],"recommendation":[1],"(SR)":[2],"aims":[3],"to":[4,58,111,159,186],"capture":[5,113],"users'":[6],"dynamic":[7],"preferences":[8],"based":[9],"on":[10,202,217],"their":[11],"historical":[12],"interactions":[13],"and":[14,35,152,193,224],"provide":[15],"personalized":[16,175],"next-item":[17],"prediction.":[18],"Multi-behavior":[19],"SR":[20],"(MBSR)":[21],"further":[22],"considers":[23],"behavior":[24,139],"types":[25],"of":[26,53,68,105,135,147,163],"user-item":[27],"interactions,":[28],"which":[29],"can":[30],"reveal":[31],"diverse":[32],"user":[33,59,114,174],"interests":[34],"alleviate":[36],"the":[37,42,51,66,75,99,127,132,156,161,164,188,195,207],"data":[38],"sparsity":[39],"issue":[40],"w.r.t.":[41,138],"target":[43,54,85,106,150,170],"purchase":[44],"behaviors.":[45],"Most":[46],"existing":[47],"MBSR":[48],"approaches":[49],"ignore":[50],"importance":[52],"items":[55],"closely":[56],"related":[57],"interests.":[60,176],"Moreover,":[61],"they":[62],"often":[63],"suffer":[64],"from":[65],"problem":[67],"limited":[69],"vector":[70],"representation":[71],"capability.":[72],"To":[73],"tackle":[74],"above":[76],"two":[77,203],"challenges,":[78],"we":[79],"propose":[80],"a":[81,120],"novel":[82],"solution":[83],"called":[84],"item-oriented":[86],"conditional":[87],"diffusion":[88,100,128,136,153,189],"differential":[89,165],"Transformer":[90],"(ICDDT).":[91],"Specifically,":[92],"our":[93,117,142,178,211],"ICDDT":[94,118,143,179,212],"introduces":[95,144],"distribution":[96],"representations":[97,172],"via":[98],"model,":[101],"allowing":[102],"effective":[103],"utilization":[104],"item":[107,171],"information":[108],"during":[109],"training":[110,162],"better":[112],"preferences.":[115],"Firstly,":[116],"achieves":[119],"more":[121],"appropriate":[122],"behavior-aware":[123],"step":[124,183,190],"selection":[125],"in":[126],"phase":[129,158],"by":[130],"distinguishing":[131],"sampling":[133,191],"distributions":[134,192],"steps":[137,154],"types.":[140],"Secondly,":[141],"three":[145],"conditions":[146],"interaction":[148],"sequences,":[149],"behaviors":[151],"into":[155],"reverse":[157],"guide":[160],"Transformer-based":[166],"approximator,":[167],"generating":[168],"denoised":[169],"as":[173],"Finally,":[177],"sets":[180],"an":[181],"inference":[182,196],"truncation":[184],"factor":[185],"fit":[187],"accelerate":[194],"process.":[197],"We":[198],"conduct":[199],"extensive":[200],"experiments":[201],"real-world":[204],"datasets,":[205,221],"where":[206],"results":[208],"show":[209],"that":[210],"significantly":[213],"outperforms":[214],"all":[215,218],"baselines":[216],"metrics.":[219],"The":[220],"source":[222],"codes":[223],"scripts":[225],"are":[226],"available":[227],"at":[228],"https://github.com/Erin-Gr/ICDDT.":[229]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-08T00:00:00"}
