{"id":"https://openalex.org/W4401864059","doi":"https://doi.org/10.1145/3637528.3671601","title":"Cross-Domain LifeLong Sequential Modeling for Online Click-Through Rate Prediction","display_name":"Cross-Domain LifeLong Sequential Modeling for Online Click-Through Rate Prediction","publication_year":2024,"publication_date":"2024-08-24","ids":{"openalex":"https://openalex.org/W4401864059","doi":"https://doi.org/10.1145/3637528.3671601"},"language":"en","primary_location":{"id":"doi:10.1145/3637528.3671601","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671601","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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":"https://openalex.org/A5016465425","display_name":"Ruijie Hou","orcid":"https://orcid.org/0000-0002-0878-9988"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ruijie Hou","raw_affiliation_strings":["Wechat, Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Wechat, Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101742899","display_name":"Zhaoyang Yang","orcid":"https://orcid.org/0000-0001-8332-1800"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoyang Yang","raw_affiliation_strings":["Wechat, Tencent, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Wechat, Tencent, Guangzhou, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105471146","display_name":"Ming Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Ming","raw_affiliation_strings":["Wechat, Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Wechat, Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101796004","display_name":"Hongyu Lu","orcid":"https://orcid.org/0000-0002-0247-2496"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyu Lu","raw_affiliation_strings":["Wechat, Tencent, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Wechat, Tencent, Guangzhou, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102591905","display_name":"Zhuobin Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuobin Zheng","raw_affiliation_strings":["Wechat, Tencent, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Wechat, Tencent, Guangzhou, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108579011","display_name":"Yu Chen","orcid":"https://orcid.org/0000-0002-5572-7173"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Chen","raw_affiliation_strings":["Wechat, Tencent, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Wechat, Tencent, Guangzhou, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035450842","display_name":"Qinsong Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinsong Zeng","raw_affiliation_strings":["Wechat, Tencent, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Wechat, Tencent, Guangzhou, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053449371","display_name":"M.-G. Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Chen","raw_affiliation_strings":["Wechat, Tencent, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Wechat, Tencent, Guangzhou, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5016465425"],"corresponding_institution_ids":["https://openalex.org/I2250653659"],"apc_list":null,"apc_paid":null,"fwci":5.5457,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.95970875,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5116","last_page":"5125"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9991999864578247,"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":0.9991999864578247,"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/T11478","display_name":"Caching and Content Delivery","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9722999930381775,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7663805484771729},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5902741551399231},{"id":"https://openalex.org/keywords/click-through-rate","display_name":"Click-through rate","score":0.4682289958000183},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3370564877986908},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.20980262756347656},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06199067831039429}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7663805484771729},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5902741551399231},{"id":"https://openalex.org/C115174607","wikidata":"https://www.wikidata.org/wiki/Q1100934","display_name":"Click-through rate","level":2,"score":0.4682289958000183},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3370564877986908},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.20980262756347656},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06199067831039429},{"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:10.1145/3637528.3671601","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671601","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2012833704","https://openalex.org/W2187089797","https://openalex.org/W2475334473","https://openalex.org/W2723293840","https://openalex.org/W2796608345","https://openalex.org/W2945772520","https://openalex.org/W2963944640","https://openalex.org/W3032044946","https://openalex.org/W3080374445","https://openalex.org/W3093945404","https://openalex.org/W3094484861","https://openalex.org/W3098400049","https://openalex.org/W3105595718","https://openalex.org/W3106252282","https://openalex.org/W3153687269","https://openalex.org/W3155450594","https://openalex.org/W3199751003","https://openalex.org/W3215053434","https://openalex.org/W4306317673","https://openalex.org/W4306317751","https://openalex.org/W4310631727"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Lifelong":[0,39,91],"sequential":[1],"modeling":[2,20],"(LSM)":[3],"has":[4],"significantly":[5],"advanced":[6,164],"recommendation":[7],"systems":[8],"on":[9,193],"social":[10],"media":[11],"platforms.":[12],"Diverging":[13],"from":[14,24,111,202],"single-domain":[15],"LSM,":[16],"cross-domain":[17,47,84,176],"LSM":[18],"involves":[19],"lifelong":[21,85],"behavior":[22],"sequences":[23,177],"a":[25,29,43,51,120,195],"source":[26],"domain":[27],"to":[28,61,147,167],"different":[30],"target":[31],"domain.":[32],"In":[33],"this":[34],"paper,":[35],"we":[36,88],"propose":[37,89],"the":[38,63,78,90,109,115,131,150,155,161,170,173,180,183,203,209],"Cross":[40,52],"Network":[41],"(LCN),":[42],"novel":[44],"approach":[45],"for":[46,76,160],"LSM.":[48],"LCN":[49,210],"features":[50],"Representation":[53],"Production":[54],"(CRP)":[55],"module":[56,117],"that":[57,208],"utilizes":[58],"contrastive":[59],"loss":[60],"improve":[62,179],"learning":[64],"of":[65,80,123,154,163,172,182,216],"item":[66,152],"embeddings,":[67],"effectively":[68,168],"bridging":[69],"items":[70,82],"across":[71,141],"domains.":[72],"This":[73,158],"is":[74],"important":[75],"enhancing":[77],"retrieval":[79],"relevant":[81],"in":[83,175,214],"sequences.":[86],"Furthermore,":[87],"Attention":[92],"Pyramid":[93],"(LAP)":[94],"module,":[95],"which":[96],"contains":[97],"three":[98,113],"cascading":[99],"attention":[100,142,165],"levels.":[101],"By":[102],"adding":[103],"an":[104,199],"intermediate":[105],"level":[106],"and":[107,126,178,198,219],"integrating":[108],"results":[110],"all":[112,185],"levels,":[114,143],"LAP":[116,135],"can":[118,136],"capture":[119],"broad":[121],"spectrum":[122],"user":[124],"interests":[125],"ensure":[127],"gradient":[128],"propagation":[129],"throughout":[130],"sequence.":[132],"The":[133],"proposed":[134],"also":[137],"achieve":[138],"remarkable":[139],"consistency":[140],"making":[144],"it":[145],"possible":[146],"further":[148],"narrow":[149],"candidate":[151],"pool":[153],"top":[156],"level.":[157],"allows":[159],"use":[162],"techniques":[166],"mitigate":[169],"impact":[171],"noise":[174],"non-linearity":[181],"representation,":[184],"while":[186],"maintaining":[187],"computational":[188],"efficiency.":[189],"Extensive":[190],"experiments":[191],"conducted":[192],"both":[194],"public":[196],"dataset":[197,201],"industrial":[200],"WeChat":[204],"Channels":[205],"platform":[206],"reveal":[207],"outperforms":[211],"current":[212],"methods":[213],"terms":[215],"prediction":[217],"accuracy":[218],"online":[220],"performance":[221],"metrics.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6}],"updated_date":"2026-03-21T08:13:44.787528","created_date":"2025-10-10T00:00:00"}
