摘要
[目的/意义]本文从融合大小数据分析的角度,深入用户偏好形成的内部机理,构建包含因果关系标签的用户画像,提高其在应用中的预测能力。[方法/过程]通过大数据分析获取用户偏好的关联关系,为量表式小数据分析提供理论假设素材并获取用户偏好的因果关系,通过语义集成形成完整的用户偏好标签体系。[结果/结论]以互联网股票投资领域进行数据实验,本文所提出的理论框架和方法能够深入用户偏好形成的心理,提高用户画像分类预测的能力。
[Purpose/Significance]From the perspective of fusion of big and small data analysis,this paper goes deep into the internal mechanism of user preference formation,constructs user portraits containing causal relationship labels,and improves its predictive ability in applications.[Method/process]The correlation relationship of user preferences is obtained through big data analysis,which provides theoretical hypothesis materials for scale-based small data analysis and obtains the causal relationship of user preferences,and forms a complete user preference label system through semantic integration.[Result/conclusion]Through the data experiment in the field of Internet stock investment,the theoretical framework and method proposed in this paper can go deep into the psychology of the formation of user preferences and improve the ability of user portrait classification and prediction.
作者
蔡皎洁
CAI Jiaojie(Hubei Engineering University,Xiaogan 432000,China;Hubei Small and Micro Enterprise Development Research Center,Xiaogan 432000,China)
出处
《情报工程》
2022年第1期100-110,共11页
Technology Intelligence Engineering
基金
湖北省科技厅软科学项目“数字普惠金融助力精准扶贫对策研究”(2019ADC148)
教育厅规划办:省社科基金前期资助项目“数字普惠金融助力精准扶贫模型研究”(19ZD057)。
