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1
Intro
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DOOH EXAMPLE
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THE IMPACT OF DOOH
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WHAT IS DYNAMIC DOOH
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DOOH HAS ITS CHALLENGES
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HOW FLEX SMARTENGINE WORKS
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THE CHALLENGE
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WITH FLEX SMARTENGINE
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THE CONTENT
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ONLINE VS DOOH
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CONTENT CATEGORIZATION
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DATA SOURCES
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GEOGRAPHIC REPRESENTATION OF AUDIENCE
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PROBABILISTIC MODELING
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POWERBI MODEL INSIGHTS DASHBOARD- DEMO
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LIBRARY OF ADS REFERENCE TABLE FOR ADS COLLECTED OVER TIME
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SMARTENGINE BACKEND AUTOMATION CHALLENGE RESOLUTION
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HOW TO MEASURE RECOMMENDED CONTENT PERFORMANCE
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SUMMARY
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KEY TAKEAWAYS
Description:
Explore the world of recommendation systems for Digital Out of Home (DOOH) advertising in this 32-minute talk by Nataliya Portman, Senior Data Scientist at Cineplex Digital Media. Dive into the challenges and strategies of reaching the right audiences with financial products and services through networks of digital screens. Learn about a probabilistic modeling approach developed at CDM and how it drives decision-making for content selection and placement. Discover the differences between online and DOOH content, content categorization techniques, and data sources used. Gain insights into geographic audience representation, the workings of Flex SmartEngine, and the use of PowerBI for model insights. Understand the challenges of backend automation and methods for measuring recommended content performance in the DOOH advertising landscape.

Recommendation Systems for Digital Out of Home Advertising

Toronto Machine Learning Series (TMLS)
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