Topics in Advanced Computing: Promise and Challenges of Recommendation Systems for the DoD

Abstract

What is a Recommendation System? Given your profile and the things youve liked in the past, what is the probability that you will click through on a recommendation? Netflix, Amazon, YouTube, Spotify, Facebook, Twitter. DNN-based personalized recommendation models comprise up to 79 percent of AI inference cycles in a production-scale data center. The Idea Behind Recommendation Systems. Given a user and an item that the user has not interacted with, what is the probability that the user will click on the item? User-item pairs with the highest predicted click-through rate are prioritized. The data is sparse, i.e., any given user has interacted with very few items.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2020
Accession Number
AD1111900

Entities

People

  • Elliot Binder
  • John Wohlbier
  • Scott McMillan
  • Tze Meng Low

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Computer Languages
  • Cyberattacks
  • Data Centers
  • Department Of Defense
  • Drone Targeting
  • Emerging Technology
  • Engineering
  • Information Warfare
  • Insider Threats
  • Materials
  • Natural Languages
  • Quantum Computing
  • Social Media
  • Social Networking Services
  • Software Development
  • Software-Defined Hardware

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Life Cycle Cost Analysis
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - DoD AI Strategy