Similarity-Based Digital Content Curation for Engaging Playlists
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Solution Overview
Problem
Content providers lack a mechanism for curating and programming their asset libraries to distribute digital content in meaningful and engaging ways.
Innovation Solution
The development of systems and methods for curating and distributing digital content, including the creation of a digital content program or playlist, by selecting and ordering a subset of assets based on similarity metrics and user behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If content providers manually curate and program their asset libraries, then the quality and meaningfulness of content distribution improves, but the time and labor required increases significantly
Solution Approach 1:
The system enables automated self-curation of content libraries by computing similarity metrics between assets and automatically generating curated collections. The computer system performs calculations to identify similar assets and creates structured playlists without requiring manual human intervention for each curation task, thus maintaining quality while reducing time investment.
Solution Approach 2:
The system transforms the curation process by changing from manual selection parameters to automated similarity metric parameters. By calculating and comparing similarity values between assets using computational methods, the system objectively determines which assets should be grouped together, replacing subjective manual judgment with quantifiable parameter-based selection.
2Quantity of substance
If content providers distribute all assets in their library, then the quantity of available content increases, but the relevance and engagement for users decreases
Solution Approach 1:
The system extracts and isolates specific subsets of assets from the complete library that are most relevant to each other based on similarity metrics. By calculating similarity values and selecting only the most closely related assets into curated collections, the system presents a refined, relevant subset rather than the entire library, thereby maintaining quantity while improving relevance.
3Productivity
If automated systems are used to curate content, then the time and labor required decreases, but the ability to create meaningful and engaging content programs deteriorates
Solution Approach 1:
The system incorporates user interaction data and engagement metrics as feedback to continuously refine and adjust the similarity metrics and curation algorithms. By monitoring how users interact with curated content and using this feedback to adjust the automated selection process, the system maintains engagement quality while benefiting from automated efficiency.
Data Source
AI summary
Disclosed herein are systems and method for curating and distributing digital content; including: digital video, music, pictures, etc. For example, presented herein are systems and methods for providing a digital content program, including a plurality of continuously provided digital assets streamed over a digital content platform. Example embodiments include: (a) curating a plurality of assets; (b) selecting a subset of assets from the plurality of assets, based on similarity metrics between assets; and (c) ordering the subset of assets into a digital content program.