| 搜索引擎全量数据的用户画像模型研究——设计与实证 |
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| 引用本文： | 吴文瀚.搜索引擎全量数据的用户画像模型研究——设计与实证[J].图书情报工作,2022,66(4):129-141. |
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| 作者姓名： | 吴文瀚 |
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| 作者单位： | 上海大学图书情报档案系 上海 200444 |
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| 摘 要： | 目的 /意义]基于某搜索引擎5亿全量数据,本文设计研究年轻用户大数据画像分析的总体模型和详细的研究流程,以建立用户画像的基本方法论.方法/过程]借助数据分析与数据验证过程的结合,通过KL散度和AIO社会学模型选取有代表性的计算样本和标签样本,并利用CH-Score和SH-Score明确算法与相关参数,利用聚类算法,...
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| 关 键 词： | 大数据 用户画像 研究模型 |
| 收稿时间： | 2021-07-02 |
| 修稿时间： | 2021-09-09 |
Research on User Portrait Model of the Full Data of Search Engines: Design and Empirical Study |
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| Wu Wenhan.Research on User Portrait Model of the Full Data of Search Engines: Design and Empirical Study[J].Library and Information Service,2022,66(4):129-141. |
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| Authors: | Wu Wenhan |
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| Institution: | Department of Library, Information and Archives, Shanghai University, Shanghai 200444 |
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| Abstract: | Purpose/significance] This research designs a research model of big data portraits of young users based on 500 million full data of a search engine, including the overall model and detailed research process to establish the basic methodology of user portraits.Method/process] With the combined process of data analysis and data verification, this paper selected representative calculation samples and label samples through KL divergence and AIO sociology model, and used CH-Score and SH-Score to clarify the algorithm and related parameters, used K-Means clustering algorithm and TGI to interpret cluster data. Finally, the association rules were used to discover the young users' car needs.Result/conclusion] This research divides young users 18-24 years old into 5 categories, 25-34 years old into 4 categories, in total of 9 groups, to verify the effectiveness of the model and process. This article completes the methodological establishment of big data user portraits from 0 to 1, and fully integrates research methods and big data methods in itl |
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| Keywords: | big data user portrait research model |
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