Interactable Text Elements in Media Comment Interfaces
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Solution Overview
Problem
Current graphical user interfaces for media assets face challenges in providing relevant recommendations, as they often rely on incomplete metadata and do not effectively utilize user interactions, such as comments, to enhance recommendation accuracy and user experience.
Innovation Solution
The system analyzes text comments to identify interactable elements, incorporating metadata from both the media asset and the device that posted the comment, and modifies the comment interface to include hyperlinks or other interactable elements, allowing users to access additional search results and supplemental content based on user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If recommendations are generated based on metadata and popularity only, then the recommendation system is simple to implement, but it fails to capture user interactions and comment data that could improve recommendation accuracy
Solution Approach 1:
The patent combines multiple data sources including metadata, popularity metrics, and user interactions (comments) into a unified recommendation system. The system merges structured metadata with unstructured comment text through text analysis, creating a comprehensive recommendation approach that leverages both simple and complex data types together to improve accuracy.
Solution Approach 2:
The patent introduces text analysis as an intermediary process that bridges the gap between unstructured comment data and the recommendation system. The text analysis component extracts meaningful terms and entities from comments, converting them into structured data that can be integrated with metadata and popularity metrics, thereby enabling improved recommendations without directly complicating the core recommendation engine.
2Adaptability or versatility
If the interface displays more recommendations and search options, then content discoverability improves, but the interface becomes more cluttered and less navigable
Solution Approach 1:
The patent segments the interface by integrating search functionality directly within the recommendation display. Instead of separating search and recommendations into different sections, the system embeds search results within the recommendation stream, allowing users to discover content through both recommendation algorithms and search queries without navigating to separate interface areas.
Solution Approach 2:
The patent makes the recommendation system multi-functional by enabling it to serve both as a passive recommendation display and an active search interface. The same interface elements that display recommended content also function as search triggers when users interact with them, allowing the interface to handle both recommendation delivery and search operations without requiring separate navigational paths.
3Productivity
If text comments are analyzed and modified to include interactable elements, then user engagement and content discovery improve, but the processing load on the media server increases
Solution Approach 1:
The patent applies preliminary text analysis to comments before they are stored or displayed. By analyzing and extracting meaningful terms from comments in advance, the system creates structured data representations that can be quickly queried later without requiring intensive real-time processing. This preliminary processing reduces the computational burden during user interactions while maintaining the ability to provide enhanced content discovery.
Data Source
AI summary
Systems and methods for improving displays of media assets are disclosed herein. In an embodiment, a system receives a plurality of text comments from a plurality of devices to which a media asset was transmitted. The system analyzes the comments to identify text strings within the text comments. The system generates interactable elements from the text strings in the text comments, such that an interaction with the text string causes display of identifiers of media assets corresponding to the text string.