{"id":"https://openalex.org/W4411551648","doi":"https://doi.org/10.1109/cscwd64889.2025.11033482","title":"Enhancing CTR Prediction with Dynamic Fusion Network","display_name":"Enhancing CTR Prediction with Dynamic Fusion Network","publication_year":2025,"publication_date":"2025-05-05","ids":{"openalex":"https://openalex.org/W4411551648","doi":"https://doi.org/10.1109/cscwd64889.2025.11033482"},"language":"en","primary_location":{"id":"doi:10.1109/cscwd64889.2025.11033482","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd64889.2025.11033482","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 28th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","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/A5100669568","display_name":"Tianhao Zhang","orcid":"https://orcid.org/0000-0003-0713-9526"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tianhao Zhang","raw_affiliation_strings":["Tianjin University of Technology,Tianjin,China"],"affiliations":[{"raw_affiliation_string":"Tianjin University of Technology,Tianjin,China","institution_ids":["https://openalex.org/I136765683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082799071","display_name":"Yingyuan Xiao","orcid":"https://orcid.org/0000-0002-5711-8638"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingyuan Xiao","raw_affiliation_strings":["Tianjin University of Technology,Tianjin,China"],"affiliations":[{"raw_affiliation_string":"Tianjin University of Technology,Tianjin,China","institution_ids":["https://openalex.org/I136765683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041936738","display_name":"Wenguang Zheng","orcid":"https://orcid.org/0000-0003-0474-6611"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenguang Zheng","raw_affiliation_strings":["Tianjin University of Technology,Tianjin,China"],"affiliations":[{"raw_affiliation_string":"Tianjin University of Technology,Tianjin,China","institution_ids":["https://openalex.org/I136765683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100669568"],"corresponding_institution_ids":["https://openalex.org/I136765683"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16509586,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1356","last_page":"1361"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9325000047683716,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9325000047683716,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5996996760368347},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5796390771865845}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5996996760368347},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5796390771865845},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cscwd64889.2025.11033482","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd64889.2025.11033482","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 28th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1613613084","https://openalex.org/W2604662567","https://openalex.org/W2788490371","https://openalex.org/W2793768763","https://openalex.org/W2898085636","https://openalex.org/W2946044191","https://openalex.org/W2964636989","https://openalex.org/W2972734859","https://openalex.org/W3035717151","https://openalex.org/W3093945404","https://openalex.org/W3119385269","https://openalex.org/W3153597579","https://openalex.org/W3164006073","https://openalex.org/W3164762341","https://openalex.org/W3208709726","https://openalex.org/W4225305708","https://openalex.org/W4384625597","https://openalex.org/W4385562515","https://openalex.org/W4400976979"],"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":{"The":[0,88,128],"forecasting":[1],"of":[2,100],"Click-Through":[3],"Rates":[4],"(CTR)":[5],"is":[6,130],"crucial":[7],"in":[8,46,53,167],"online":[9],"advertising":[10],"and":[11,17,28,58,79,86,113,117,125,142,161],"recommendation":[12],"systems,":[13],"significantly":[14,157],"impacting":[15],"revenue":[16],"user":[18,38],"experience.":[19],"Traditional":[20],"CTR":[21,137],"models":[22,138],"rely":[23],"on":[24,151],"simple":[25],"feature":[26,47,84,105],"representations":[27],"static":[29],"interactions,":[30],"making":[31],"it":[32,49],"difficult":[33],"to":[34,55,82,91,109,122,132,135],"accurately":[35],"capture":[36],"complex":[37],"behaviors.":[39],"Although":[40],"deep":[41],"learning":[42],"has":[43],"made":[44],"progress":[45],"processing,":[48],"still":[50],"faces":[51],"challenges":[52],"adapting":[54],"dynamic":[56,168],"environments":[57],"maintaining":[59],"model":[60],"stability.":[61],"This":[62],"paper":[63],"introduces":[64],"the":[65],"Dynamic":[66,75],"Fusion":[67],"Prediction":[68],"Network":[69],"(DFPN),":[70],"which":[71],"innovatively":[72],"employs":[73],"a":[74,96],"Context":[76],"Encoder":[77],"(DCE)":[78],"FusionGate":[80,102],"mechanism":[81],"enhance":[83],"representation":[85,99],"interaction.":[87],"DCE":[89],"adapts":[90],"varying":[92],"contexts,":[93],"allowing":[94],"for":[95,147],"more":[97],"personalized":[98],"features.":[101],"further":[103],"improves":[104,158],"importance":[106],"identification,":[107],"contributing":[108],"enhanced":[110],"prediction":[111],"accuracy":[112],"robustness.":[114],"Additionally,":[115],"dropout":[116],"layer":[118],"normalization":[119],"are":[120],"integrated":[121],"mitigate":[123],"overfitting":[124],"improve":[126],"generalization.":[127],"DFPN":[129,156],"designed":[131],"be":[133],"orthogonal":[134],"existing":[136],"such":[139],"as":[140],"FM":[141],"DeepFM,":[143],"enabling":[144],"flexible":[145],"integration":[146],"performance":[148,166],"enhancement.":[149],"Experiments":[150],"public":[152],"benchmarks":[153],"demonstrate":[154],"that":[155],"accuracy,":[159],"generalization,":[160],"stability,":[162],"confirming":[163],"its":[164],"superior":[165],"environments.":[169]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
