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HIFM For Mobile Ads.pdf

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Preview of HIFM for Mobile Ads
🔗 Source: web.archive.org
📊 Size: 556 KB
👤 Author: roentaryo
⬇️ Downloads: 129

Summary

Mobile advertising has seen dramatic growth, and predicting ad response is crucial for maximizing revenue. The task of predicting ad response is challenging due to dynamic data, cold-start situations, and the need for robust regression estimation and good ranking. A Hierarchical Importance-aware Factorization Machine (HIFM) is developed to address these challenges, incorporating importance weights and hierarchical learning. HIFM outperforms contemporary temporal latent factor models and demonstrates the efficacy of importance-aware and hierarchical learning in improving overall prediction and prediction in cold-start scenarios.

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Description

Mobile advertising has seen dramatic growth, and predicting ad response is crucial for maximizing revenue.

Technical Information

  • File Format: PDF
  • File Size: 556 KB
  • Pages: 10
  • Language: EN
  • Author: roentaryo
  • Total Downloads: 129
  • Last Updated: 10 hours ago

Document Overview

This PDF document about HIFM for Mobile Ads provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into HIFM for Mobile Ads.

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HIFM guideHIFM tutorialMobile guideMobile tutorial

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