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All Journal International Journal of Applied and Advanced Multidisciplinary Research (IJAAMR)
Chaitali Khachane
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Humanities Civil Engineering, Building, Construction & Architecture Economics, Econometrics & Finance Education Social Sciences

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Targeted Display Advertising using Machine Learning Chaitali Khachane
International Journal of Applied and Advanced Multidisciplinary Research Vol. 1 No. 3 (2023): November 2023
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijaamr.v1i3.715

Abstract

This paper delves into the intricate challenges of problem formulation and data representation in the context of a large-scale machine learning system for targeted display advertising. Unlike traditional models, this system is not just conceptual but has been operational for years across thousands of advertising campaigns. Since obtaining ideal training data is cost-prohibitive, data is sourced from related domains and tasks and then adapted for the target task. The paper outlines the architecture of this multi-stage transfer learning system, emphasizing the problem formulation aspects. Extensive experiments demonstrate the value of each transfer stage. Real-world results with diverse advertising clients from various industries showcase the system's performance. The paper concludes with valuable insights gained from over half a decade of work on this complex, widely deployed machine learning system.
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