用户信息访问行为估计的逐步适应模型

Jing Chen, Roman Y. Shtykh, Qun Jin
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引用次数: 4

摘要

在本研究中,我们提出了一个渐进适应模型来估计用户信息访问行为。以每天为单位收集每个用户的各种用户信息访问数据,并按短期、中期、长期、显著和异常类别进行分析。然后基于全贝叶斯估计对预处理数据进行分析,建立模型。最后给出了实验仿真结果,验证了所提模型的可操作性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Gradual Adaption Model for Estimation of User Information Access Behavior
In this study, we propose a gradual adaption model for estimation of user information access behavior. A variety of userspsila information access data are collected by unit of a day for each user, and analyzed in terms of short, medium, long periods, and by remarkable and exceptional categories. The proposed model is then established by analyzing the pre-processed data based on Full Bayesian Estimation. We further present experimental simulation results, and show the operability and effectiveness of our proposed model.
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