存在徽章的连续时间用户建模：一种概率方法
Continuous-Time User Modeling in the Presence of Badges: A Probabilistic Approach
摘要：
用户建模在向用户提供定制的Web服务和提高他们的参与度方面起着重要的作用。然而，大多数用户模型在文献中没有明确考虑用户的时间行为。最近，连续时间用户建模得到了相当大的关注，许多用户行为模型已经提出了基于时间点过程。然而，典型的基于点过程的模型往往考虑了同伴影响力和内容对用户参与的影响，而忽略了其他因素。游戏化元素是被忽视的因素之一，而它们对用户参与在线服务有很大的影响。在本文中，我们提出了相互依赖的多维时间点过程，捕获的影响，除了同行的影响和内容因素的徽章对用户参与。我们提出的过程中，以社区为基础的问答网站的用户行为模型，并提出了一个推理算法的基础上变分EM，可以有效地学习模型参数。对从Stack Overflow收集的合成数据和真实数据进行的大量实验表明，我们的推理算法有效地学习了参数，并且与替代方案相比，所提出的方法可以更好地预测用户行为。
英文摘要：
User modeling plays an important role in delivering customized web services to the users and improving their engagement. However, most user models in the literature do not explicitly consider the temporal behavior of users. More recently, continuous-time user modeling has gained considerable attention and many user behavior models have been proposed based on temporal point processes. However, typical point process based models often considered the impact of peer influence and content on the user participation and neglected other factors. Gamification elements, are among those factors that are neglected, while they have a strong impact on user participation in online services. In this paper, we propose interdependent multi-dimensional temporal point processes that capture the impact of badges on user participation besides the peer influence and content factors. We extend the proposed processes to model user actions over the community based question and answering websites, and propose an inference algorithm based on Variational-EM that can efficiently learn the model parameters. Extensive experiments on both synthetic and real data gathered from Stack Overflow show that our inference algorithm learns the parameters efficiently and the proposed method can better predict the user behavior compared to the alternatives.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
