Content Item Banner Selection for Spoiler-Free Binge Viewing
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Solution Overview
Problem
Existing content item delivery systems face challenges in providing user-friendly banners that avoid spoilers, leading to a poor user experience, especially in binge-watching sessions where users may encounter unexpected plot developments.
Innovation Solution
Systems and methods generate content item banners based on session type and content item type, using user profiles and metadata to identify non-spoiler banners, apply masking elements, and update banners based on consumption progress.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a banner comprising a male lead character is displayed for a content item, then the banner attracts user attention and provides information about the content item, but it may reveal plot spoilers to users consuming the series for the first time
Solution Approach 1:
The system dynamically selects banners based on detected session types. When binge-watching is detected, spoiler-free banners are selected; when casual viewing is detected, standard banners are selected. This dynamic adaptation resolves the contradiction by making banner selection context-dependent rather than static.
Solution Approach 2:
The system performs preliminary detection of session type and user consumption patterns before selecting a banner. By analyzing viewing history and detecting binge-watching patterns in advance, the system prepares and selects appropriate spoiler-free banners before the user encounters them, preventing information leakage.
2Reliability
If the system detects binge-watching sessions and selects spoiler-free banners, then user experience is improved by maintaining suspense, but the system complexity increases due to session detection and banner selection logic
Solution Approach 1:
The system segments banner selection into distinct paths based on session type. One path handles binge-watching sessions with spoiler-free banners, another handles casual viewing with standard banners. This segmentation simplifies the overall system by creating clear, manageable decision branches rather than a single complex selection process.
Solution Approach 2:
The system changes the selection parameter from static user profile data to dynamic session type detection. By monitoring viewing patterns, time intervals between episodes, and consumption speed, the system adapts the banner selection parameter based on actual usage behavior, improving reliability without requiring overly complex manual configuration.
3Adaptability or versatility
If multiple banners are associated with a single content item and selection is based on user profile, then personalized content delivery is achieved, but it may inadvertently provide spoilers to new viewers
Solution Approach 1:
The system introduces session type detection as an intermediary layer between user profile and banner selection. Instead of directly selecting banners based on user profile alone, the system first detects the current session type and uses this intermediate information to filter or select from available banners, preventing spoilers while maintaining personalization.
Solution Approach 2:
The banner selection system serves multiple functions: it personalizes content delivery based on user profiles, detects session types, prevents spoilers, and adapts to different viewing contexts. By making the system multi-functional, it resolves the contradiction by integrating what would otherwise be separate systems into a unified solution.
Data Source
AI summary
Systems and methods are provided for generating a content item banner for display based on a session type and a content item type. A user profile is accessed at a computing device, and a session type associated with consumption of at least a content item of a plurality of content items is determined based on the user profile. A content item type associated with the plurality of content items is determined, and a content item banner for a subsequent content item of the plurality of content items is identified based on the session type and the content item type. The content item banner is generated for display.