Use Case Configuration for Content Selection Interfaces
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Solution Overview
Problem
The vast array of content options available to users through content providers leads to viewer dissatisfaction as users often stick to familiar content rather than exploring new options, resulting in inefficient use of content curation efforts.
Innovation Solution
A method and system that utilize historical user action data to configure and optimize use cases for content selection interfaces, allowing for personalized content recommendations and improved user engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If content providers curate use cases that define content groups for presentation in EPGs, then content organization and accessibility are improved, but user satisfaction deteriorates because users continue to view only familiar content and do not explore new options
Solution Approach 1:
The system dynamically adjusts use case parameters based on real-time user feedback and historical data. Instead of static content groupings, the use cases evolve and adapt their parameters (such as content categories, time windows, and selection criteria) to balance familiarity and novelty, enabling users to discover new content while maintaining accessibility to preferred content types.
Solution Approach 2:
The system changes key parameters of use cases including the diversity weight, time window for recent views, and category selection based on user behavior patterns. By adjusting these parameters dynamically, the system optimizes the balance between showing familiar content (high accessibility) and introducing new content (high exploration), resolving the contradiction between ease of operation and adaptability.
2Productivity
If content providers create and release use cases with predefined parameters, then content curation efficiency is improved, but development resource waste increases because insights into use case performance arrive too late to optimize parameters
Solution Approach 1:
The system implements continuous feedback loops where user interactions with content (views, ratings, time spent) are immediately captured and fed back into the use case parameter optimization process. This real-time feedback enables rapid iteration and adjustment of use case parameters without waiting for post-release analysis, eliminating development resource waste while maintaining high curation efficiency.
Solution Approach 2:
The system performs preliminary testing and parameter optimization using historical user data before fully deploying use cases. By simulating user responses and pre-optimizing parameters based on past behavior patterns, the system reduces the risk of creating ineffective use cases, thereby minimizing development resource waste while maintaining productive content curation workflows.
3Adaptability or versatility
If users are presented with a large choice of content from multiple sources, then content variety is improved, but user time consumption increases as users spend more time searching for suitable new content
Solution Approach 1:
The system automatically performs content filtering and recommendation based on user profiles and historical behavior, eliminating the need for users to manually search through vast content libraries. The use cases self-adjust to present personalized content selections that balance variety and relevance, allowing users to access diverse content quickly without investing significant time in search activities.
Solution Approach 2:
The system pre-processes and organizes content into optimized use case groups based on user preferences and historical data before users need to access it. By performing preliminary content selection and organization, the system reduces the effective search space for users, maintaining high content variety while minimizing the time users spend searching for suitable content.
Data Source
AI summary
A method, system and computer program product for determining use cases for a content selection interface that provides user selectable indications of content available from a content provider according to the use cases. The indications of available content are selectable by a user to have the content provided to the user by the content provider. The method comprises, using a computing system: accessing, from at least one computer readable data store, historical data representing previous user actions of a plurality of users using a content selection interface; identifying, using the computing system, one or more attributes associated with the user actions from the historical data; and using the identified attributes to configure one or more use cases for providing indications of available content on the content selection interface.