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Spatio-temporal models for estimating click-through rate

Published: 20 April 2009 Publication History

Abstract

We propose novel spatio-temporal models to estimate click-through rates in the context of content recommendation. We track article CTR at a fixed location over time through a dynamic Gamma-Poisson model and combine information from correlated locations through dynamic linear regressions, significantly improving on per-location model. Our models adjust for user fatigue through an exponential tilt to the first-view CTR (probability of click on first article exposure) that is based only on user-specific repeat-exposure features. We illustrate our approach on data obtained from a module (Today Module) published regularly on Yahoo! Front Page and demonstrate significant improvement over commonly used baseline methods. Large scale simulation experiments to study the performance of our models under different scenarios provide encouraging results. Throughout, all modeling assumptions are validated via rigorous exploratory data analysis.

References

[1]
D. Agarwal, B.-C. Chen, P. Elango, and et al. Online models for content optimization. In NIPS, 2008.
[2]
P. Auer, N. Cesa-Bianchi, and P. Fischer. Finite-time analysis of the multiarmed bandit problem. Machine Learning, 2002.
[3]
Y. Benjamini and Y. Hochberg. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society B, 1995.
[4]
C.A.Colin and P.K.Trivedi. Regression Analysis of Count Data. Cambridge University Press, 1998.
[5]
J. M. Chambers. Software for Data Analysis: Programming with R. Springer, 2008.
[6]
C.R.Rao. Linear Statistical Inference and Its Applications. Wiley, 2002.
[7]
D.K.Stangl and D.A.Berry. Meta-analysis in Medicine and Health Policy. CRC Press, 2000.
[8]
D.Lambert and C.Liu. Adaptive thresholds: Monitoring streams of network counts. Journal of the American Statistical Association, 2006.
[9]
C. Kaufman, V. Ventura, and R. Kass. Spline-based non-parametric regression for periodic functions and its application to directional tuning of neurons. Statistics in Medicine, 2005.
[10]
Q. Mei and K. W. Church. Entropy of search logs: how hard is search? with personalization? with backoR? In WSDM, 2008.
[11]
M.West and J.Harrison. Bayesian Forecasting and Dynamic Models. Springer--Verlag, 1997.
[12]
F. Radlinski and T. Joachims. Active exploration for learning rankings from clickthrough data. In KDD, 2007.
[13]
M. Richardson, E. Dominowska, and R. Ragno. Predicting clicks: estimating the click-through rate for new ads. In WWW, 2007.
[14]
S.P.Ellner and Y.Seifu. Using spatial statistics to select model complexity. Journal of Computational and Graphical Statistics, 2002.
[15]
F. Wu and B. A. Huberman. Novelty and collective attention. In Proceedings of National Academy of Sciences, 2007.
[16]
F. Wu and B. A. Huberman. Popularity, novelty and attention. In EC. ACM, 2008.

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cover image ACM Conferences
WWW '09: Proceedings of the 18th international conference on World wide web
April 2009
1280 pages
ISBN:9781605584874
DOI:10.1145/1526709

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 April 2009

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Author Tags

  1. content recommendation
  2. ctr positional correlation

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  • (2024)Bandits with concave aggregated rewardProceedings of the Thirty-Third International Joint Conference on Artificial Intelligence10.24963/ijcai.2024/597(5398-5406)Online publication date: 3-Aug-2024
  • (2023)Non-stationary bandits with auto-regressive temporal dependencyProceedings of the 37th International Conference on Neural Information Processing Systems10.5555/3666122.3666468(7895-7929)Online publication date: 10-Dec-2023
  • (2023)Workshop on Learning and Evaluating Recommendations with Impressions (LERI)Proceedings of the 17th ACM Conference on Recommender Systems10.1145/3604915.3608756(1248-1251)Online publication date: 14-Sep-2023
  • (2023)Fragment and Integrate Network (FIN): A Novel Spatial-Temporal Modeling Based on Long Sequential Behavior for Online Food Ordering Click-Through Rate PredictionProceedings of the 32nd ACM International Conference on Information and Knowledge Management10.1145/3583780.3615478(4688-4694)Online publication date: 21-Oct-2023
  • (2022)Sparse Attentive Memory Network for Click-through Rate Prediction with Long SequencesProceedings of the 31st ACM International Conference on Information & Knowledge Management10.1145/3511808.3557095(3312-3321)Online publication date: 17-Oct-2022
  • (2022)Traffic Anomaly Prediction Based on Joint Static-Dynamic Spatio-Temporal Evolutionary LearningIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.3150272(1-1)Online publication date: 2022
  • (2022)Click-through rate prediction in online advertisingInformation Processing and Management: an International Journal10.1016/j.ipm.2021.10285359:2Online publication date: 9-May-2022
  • (2021)SAR-NetProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3481948(4094-4103)Online publication date: 26-Oct-2021
  • (2021)A Real-World Implementation of Unbiased Lift-based Bidding System2021 IEEE International Conference on Big Data (Big Data)10.1109/BigData52589.2021.9671800(1877-1888)Online publication date: 15-Dec-2021
  • (2021)An embedded bandit algorithm based on agent evolution for cold-start problemInternational Journal of Crowd Science10.1108/IJCS-03-2021-00055:3(228-238)Online publication date: 5-Aug-2021
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