Webpage depth-level dwell time prediction
Document Type
Conference Proceeding
Publication Date
10-24-2016
Abstract
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 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.
Identifier
84996528115 (Scopus)
ISBN
[9781450340731]
Publication Title
International Conference on Information and Knowledge Management Proceedings
External Full Text Location
https://doi.org/10.1145/2983323.2983878
First Page
1937
Last Page
1940
Volume
24-28-October-2016
Grant
1565478
Fund Ref
National Science Foundation
Recommended Citation
Wang, Chong; Kalra, Achir; Borcea, Cristian; and Chen, Yi, "Webpage depth-level dwell time prediction" (2016). Faculty Publications. 10200.
https://digitalcommons.njit.edu/fac_pubs/10200
