{"id":"https://openalex.org/W4409983024","doi":"https://doi.org/10.1137/1.9781611978520.20","title":"CDSRNP: Cross-Domain Sequential Recommendation via Neural Process","display_name":"CDSRNP: Cross-Domain Sequential Recommendation via Neural Process","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4409983024","doi":"https://doi.org/10.1137/1.9781611978520.20"},"language":"en","primary_location":{"id":"doi:10.1137/1.9781611978520.20","is_oa":false,"landing_page_url":"https://doi.org/10.1137/1.9781611978520.20","pdf_url":null,"source":{"id":"https://openalex.org/S4306463922","display_name":"Society for Industrial and Applied Mathematics eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"ebook platform"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 SIAM International Conference on Data Mining (SDM)","raw_type":"book-chapter"},"type":"book-chapter","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/A5100363265","display_name":"Haipeng Li","orcid":"https://orcid.org/0000-0001-7856-4488"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haipeng Li","raw_affiliation_strings":["Equal contributions to this work","Nanjing University of Science and Technology"],"affiliations":[{"raw_affiliation_string":"Equal contributions to this work","institution_ids":[]},{"raw_affiliation_string":"Nanjing University of Science and Technology","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017144784","display_name":"Jiangxia Cao","orcid":"https://orcid.org/0000-0003-2681-0119"},"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":[],"is_corresponding":false,"raw_author_name":"Jiangxia Cao","raw_affiliation_strings":["Equal contributions to this work","Kuaishou Technology"],"affiliations":[{"raw_affiliation_string":"Equal contributions to this work","institution_ids":[]},{"raw_affiliation_string":"Kuaishou Technology","institution_ids":["https://openalex.org/I4401726859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101609832","display_name":"Yiwen Gao","orcid":"https://orcid.org/0000-0001-5950-0040"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiwen Gao","raw_affiliation_strings":["Nanjing University of Science and Technology"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082653046","display_name":"Yunhuai Liu","orcid":"https://orcid.org/0000-0002-1180-8078"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunhuai Liu","raw_affiliation_strings":["Peking University"],"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088461583","display_name":"Shuchao Pang","orcid":"https://orcid.org/0000-0002-5668-833X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuchao Pang","raw_affiliation_strings":["Nanjing University of Science and Technology"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100363265"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1807007,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"213","last_page":"222"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9855999946594238,"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/T10028","display_name":"Topic Modeling","score":0.9855999946594238,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9850999712944031,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9527000188827515,"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":0.594019889831543},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5170984268188477},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.48205527663230896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34424838423728943},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13356080651283264},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.05679023265838623}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.594019889831543},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5170984268188477},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.48205527663230896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34424838423728943},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13356080651283264},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.05679023265838623},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1137/1.9781611978520.20","is_oa":false,"landing_page_url":"https://doi.org/10.1137/1.9781611978520.20","pdf_url":null,"source":{"id":"https://openalex.org/S4306463922","display_name":"Society for Industrial and Applied Mathematics eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"ebook platform"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 SIAM International Conference on Data Mining (SDM)","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"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/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Cross-Domain":[0],"Sequential":[1],"Recommendation":[2],"(CDSR)":[3],"is":[4,89,103,120],"a":[5,17,67,78,101,159,163,185,207,258,269],"hot":[6],"topic":[7],"in":[8,110,128,290],"sequence-based":[9],"user":[10,73,95,126,244,249],"interest":[11,271],"modeling,":[12],"which":[13,42,76,140],"aims":[14],"at":[15],"utilizing":[16],"single":[18],"model":[19,116,124],"to":[20,54,91,123,137,148,151,153,169,177,223,234,261,274,279],"predict":[21],"the":[22,30,46,56,71,82,106,142,171,199,220,231,236,247,276],"next":[23],"items":[24],"for":[25],"different":[26],"domains.":[27],"To":[28,180],"tackle":[29],"CDSR,":[31],"many":[32],"methods":[33,289],"are":[34,132],"focused":[35],"on":[36,45],"domain":[37,86,94,135,264],"overlapped":[38,64,87,216],"users\u2019":[39,145,175,217,226,277],"behaviors":[40,127,136,176,218,253],"fitting,":[41],"heavily":[43],"relies":[44],"same":[47],"user\u2019s":[48],"different-domain":[49],"item":[50],"sequences":[51,147],"collaborating":[52],"signals":[53],"capture":[55],"synergy":[57],"of":[58,70,85,173,201],"cross-domain":[59,154,237],"item-item":[60],"correlation.":[61],"Indeed,":[62],"these":[63],"users":[65,88,112],"occupy":[66],"small":[68,83],"fraction":[69],"entire":[72],"set":[74,222],"only,":[75],"introduces":[77],"strong":[79],"assumption":[80],"that":[81,285],"group":[84],"enough":[90],"represent":[92],"all":[93],"behavior":[96,146],"characteristics.":[97],"However,":[98],"intuitively,":[99],"such":[100,158],"suggestion":[102],"biased,":[104],"and":[105,165,203],"insufficient":[107],"learning":[108],"paradigm":[109],"non-overlapped":[111,125,174,251],"will":[113],"inevitably":[114],"limit":[115],"performance.":[117],"Further,":[118],"it":[119],"not":[121],"trivial":[122],"CDSR":[129,187],"because":[130],"there":[131],"no":[133],"other":[134,263],"collaborate":[138],"with,":[139],"causes":[141],"observed":[143,215],"single-domain":[144],"be":[149],"hard":[150],"contribute":[152],"knowledge":[155],"mining.":[156],"Considering":[157],"phenomenon,":[160],"we":[161,183,211,229,267],"raise":[162],"challenging":[164],"unexplored":[166],"question:":[167],"How":[168],"unleash":[170],"potential":[172],"empower":[178,224],"CDSR?":[179],"this":[181],"end,":[182],"propose":[184],"novel":[186],"framework":[188],"with":[189],"Neural":[190],"Processes":[191],"(NP),":[192],"briefly":[193],"termed":[194],"CDSRNP,":[195],"where":[196],"NP":[197,232],"combines":[198],"advantages":[200],"meta-learning":[202,208],"stochastic":[204],"processes.":[205],"As":[206],"based":[209],"method,":[210],"first":[212],"sample":[213],"some":[214],"as":[219],"support":[221],"query":[225,248],"prediction.":[227,281],"Next,":[228],"employ":[230],"principle":[233],"align":[235],"correlation":[238],"prior/posterior":[239],"distributions":[240],"generated":[241],"by":[242],"support/query":[243],"sets,":[245],"thus":[246],"(e.g.,":[250],"user)":[252],"sequence":[254],"could":[255],"also":[256],"establish":[257],"straight":[259],"bridge":[260],"connect":[262],"items.":[265],"Additionally,":[266],"design":[268],"fine-grained":[270],"adaptive":[272],"layer":[273],"identify":[275],"interests":[278],"enhance":[280],"Experimental":[282],"results":[283],"illustrate":[284],"CDSRNP1":[286],"outperforms":[287],"state-of-the-art":[288],"two":[291],"real-world":[292],"datasets.":[293]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}