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面向海量數(shù)據(jù)場(chǎng)景的生成對(duì)抗網(wǎng)絡(luò)推薦算法

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引用格式:,,.面向海量數(shù)據(jù)場(chǎng)景的生成對(duì)抗網(wǎng)絡(luò)推薦算法[J].現(xiàn)代電子技術(shù),2025,48(10):71-75.

關(guān)鍵詞:海量數(shù)據(jù)場(chǎng)景;生成對(duì)抗網(wǎng)絡(luò);長(zhǎng)短期記憶網(wǎng)絡(luò);推薦算法;動(dòng)態(tài)序列;個(gè)性化推薦;目標(biāo)函數(shù)中圖分類(lèi)號(hào):TN919.2-34;TP391 文獻(xiàn)標(biāo)識(shí)碼:A 文章編號(hào):1004-373X(2025)10-0071-05

Abstract:Masivedataoftencontainscomplexuserbehaviorpatterns,itematributesandtheirrelationships,whichoften havenon-linearcharacteristics.Traditional generativeadversarial network (GAN)mayfacechallngesinnonlinear modeling whenprocesingsequencedata.Inordertoefectivelycapturethelong-shortterminterestchangesofusers,enrichthediversity ofcontent,enhancetheprocessingabilityandstabilityinmassivedatascenarios,agenerativeadversarialnetwork recommendtionalgorithmformassivedatascenariosisproposed.Inthelong-shorttermmemorynetwork(LSTM),theuser's behaviorpaterns towardsthedatasceneareusedasinputtooutput the dynamicsequenceof long-shorttermdatascenesof interesttotheuser.TheLSTMiscombinedwithGANtoformanL-GANrecommendationmodel.Inthismodel,thelong-short termdynamicsequencesoutputbyLSTMareinputintothegeneratorofGAN,andfalsesamplessimilartorealdatascenarios aregeneratedbyoptimizingthelossfunction.Thefakesamplesareinputintothediscriminatortogetherwiththerealdata scenes,andtheauthenticityisidentifiedbymeansofitsobjectivefunction.Afterrepeatedcompetitionandtraining,thegeerator anddiscriminatorcanformanaccuraterecommendationnetwork,soastofinallyoutputarecommendationlistofdatascenesthat meetthe user's interests.Theexperimental resultsshow that the proposed algorithmcan acuratelycapture the nedsof users when processing massive data scenes,and make eficient and comprehensive personalized recommendations.

Keywords:masivedatascenario;generative adversarial network;long-short term memory network;recommendation algorithm;dynamic sequence;personalized recommendation;objective function

0 引言

面向海量數(shù)據(jù)場(chǎng)景的推薦算法能夠幫助企業(yè)和平臺(tái)更精準(zhǔn)地理解用戶需求,為產(chǎn)品研發(fā)和決策提供有力支持。(剩余5746字)

目錄
monitor