谷歌浏览器插件
订阅小程序
在清言上使用

Webpage Depth-level Dwell Time Prediction

International Conference on Information and Knowledge Management(2016)

引用 13|浏览87
暂无评分
摘要
The amount of time spent by users at specific page depths within webpages, called dwell time, can be used by web publishers to decide where to place online ads and what type of ads to place at different depths within a webpage. This paper presents a model to predict the dwell time for a given "user, webpage, depth" triplet based on historic data collected by publishers. Dwell time prediction is difficult due to user behavior variability and data sparsity. We adopt the Factorization Machines model because it is able to capture the interaction between users and webpages, overcome the data sparsity issue, and provide flexibility to add auxiliary information such as the visible area of a user's browser. Experimental results using data from a large web publisher demonstrate that our model outperforms deterministic and regression-based comparison models.
更多
查看译文
关键词
Computational Advertising,User Behavior,Data Mining
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要