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基于Agent模型的电力企业干部资质画像构建方法 被引量:1

Construction Method of Qualification Portrait of Power Enterprise Cadres Based on Agent Model
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摘要 构建电力企业干部资质画像时,大多忽略了电力企业干部资质信息清洗的必要性,导致画像的信息覆盖率低、F1系数低、构建时间长,由此,提出基于Agent模型的电力企业干部资质画像构建方法。引入Agent模型,建立电力企业干部资质相关信息采集系统,利用堆栈式降噪自编码器清洗电力企业干部资质信息,通过隐半马尔可夫模型提取电力企业干部的行为特征,将提取的特征输入长短期记忆网络LSTM中,构建电力企业干部资质画像。实验结果表明,所提方法的信息覆盖率高、F1系数高、画像构建时间短。 In constructing the power enterprise cadre qualification portrait,most of them neglect the necessity of cleaning the power enterprise cadre qualification information,which leads to the low information coverage rate,low F1 coefficient and long construction time.Therefore,this paper proposes a construction method of power enterprise cadre qualification portrait based on agent model.The agent model is introduced to establish the power enterprise cadre qualification information collection system.The stack noise reduction self-encoder is used to clean the power enterprise cadre qualification information.The hidden semi Markovian model is used to extract the behavior characteristics of power enterprise cadres.The extracted features are input into the long-term and short-term memory network LSTM to construct the power enterprise cadre qualification portrait.The experimental results show that the proposed method has high information coverage,high F1 coefficient and short portrait construction time.
作者 冯志鹏 严宇平 陈文安 苏华权 FENG Zhipeng;YAN Yuping;CHEN Wenan;SU Huaquan(Guangdong Electric Power Information Technology Co. Ltd., Guangzhou 510600, China;Guangdong Power Grid Co. Ltd., Guangzhou 510600, China;Information Center of Guangdong Power Grid Co. Ltd., Guangzhou 510600, China)
出处 《微型电脑应用》 2022年第6期120-123,共4页 Microcomputer Applications
关键词 AGENT模型 电力企业 用户画像 堆栈式降噪编码器 隐马尔可夫模型 LSTM Agent model power enterprise user portrait stacked noise reduction encoder hidden Markovian model
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  • 1吴垠.关于中国消费者分群范式(China-Vals)的研究[J].南开管理评论,2005,8(2):9-15. 被引量:72
  • 2Idc.Worldwide Quarterly Mobile Phone Tracker.2014.
  • 3Lee S C,Paik J,Ok J,et al.Efficient mining of user behav-iors by temporal mobile access patterns [J].Intl J.ComputerScience Security,2007,7 (2):285-291.
  • 4Chen T S,Chou Y S,Chen T C.Mining user movement be-havior patterns in a mobile service environment [J].Systems,Man and Cybernetics,Part A:Systems and Humans,IEEETransactions on,2012,42 (1):87-101.
  • 5Yava?G,Katsaros D,Ulusoy,et al.A data mining ap-proach for location prediction in mobile environments [J].Da-ta & Knowledge Engineering,2005,54 (2):121-146.
  • 6Baratchi M,Meratnia N,Havinga P J M.Recognition of pe-riodic behavioral patterns from streaming mobility data [M].Mobile and Ubiquitous Systems:Computing, Networking,and Services.Springer International Publishing,2014:102-115.
  • 7Li Z,Ding B,Han J,et al. Mining periodic behaviors formoving objects [C]∥Proceedings of the 16th ACM SIGKDDinternational conference on Knowledge discovery and data min-ing.ACM,2010:1099-1108.
  • 8Zhang M,Kao B,Cheung D W,et al.Mining periodic pat-terns with gap requirement from sequences [J].ACM Trans-actions on Knowledge Discovery from Data (TKDD),2007,1(2):7.
  • 9Ji Y,Zhang C,Zuo Z,et al. Mining user daily behaviorbased on location history [C] ∥Communication Technology(ICCT),2012IEEE 14th International Conference on.IEEE,2012:881-886.
  • 10Zhu Y,Zhang Y,Shang W,et al.Trajectory enabled serv-ice support platform for mobile usersbehavior pattern mining[C]. Mobile and Ubiquitous Systems:Networking & Serv-ices,MobiQuitous,2009.MobiQuitous09.6th Annual In-ternational.IEEE,2009:1-10.

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