Empowering content search: Leveraging the potential of machine learning

Meenakshi Jindal, Varun Sekhri and Tiffany Low
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Meenakshi Jindal: Netflix, Inc., USA
Varun Sekhri: Netflix, Inc., USA
Tiffany Low: Netflix, Inc., USA

Journal of Digital Media Management, 2023, vol. 12, issue 2, 116-126

Abstract: In the digital age, the power of machine learning is harnessed to transform content search capabilities. This integration heralds a new era for content creation tools, granting editors and creators access to granular, frame-level content insights. These capabilities enable precision adjustments, enhancing the final product’s efficiency and quality. Recent years have witnessed remarkable shifts in using machine-generated data within media tools. However, harnessing the full potential of machine-learning techniques poses challenges due to the vast and diverse data generated by many algorithms. In response, Netflix has pioneered a groundbreaking solution: the Media Understanding Platform. This platform is a unifying abstraction layer across all Netflix studio applications, bridging the gap between client and machine-learning platforms. This paper illustrates the platform’s design and prowess through real-world examples of promotional media tools that enrich content discovery within Netflix’s expansive catalogue, offering a glimpse into the future of content search.

Keywords: digital assets search; machine learning; creative tools; standard schema; centralised platform (search for similar items in EconPapers)
JEL-codes: M11 M15 (search for similar items in EconPapers)
Date: 2023
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