Radial Media Browsing Interface with Affinity-Based Grouping
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Solution Overview
Problem
Traditional media content browsing methods, such as linear grid formats, become cumbersome when dealing with large collections, requiring users to scroll through numerous channels or pages to find specific content, and often fail to group channels by type, making it difficult for users to locate items of interest efficiently.
Innovation Solution
A system that allows users to select affinities and weights for metadata, arranging items in a view based on how well they fit the user's preferences, using a combination of affinity gels and a fisheye lens for visual representation, enabling quick identification of relevant media content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a linear grid format is used to display media content, then the browsing interface is simple to implement, but it becomes increasingly difficult for consumers to locate items of interest as the amount of content grows
Solution Approach 1:
The patent transitions from a traditional linear grid format to a radial visualization where content is organized around a central focal point. This dimensional change allows content to be displayed in a circular pattern with the most relevant items positioned at the center, enabling users to quickly locate interesting content without scrolling through numerous pages in a linear arrangement.
Solution Approach 2:
The patent applies different visual properties to different regions of the display. The central region highlights the most relevant content with enhanced visibility, while peripheral regions display less prioritized content. This local differentiation allows users to immediately focus on high-value content while still having access to the full collection.
2Ease of operation
If channels are not grouped by type in traditional browsers, then the display format remains uniform and simple, but users have to scroll through various pages to find channels of specific types
Solution Approach 1:
The system pre-groups content by type and automatically positions relevant content in the radial display based on user context and preferences. Before the user even begins browsing, content is organized into logical groupings (e.g., children's programming, news, sports) and positioned accordingly, eliminating the need for users to manually search through unorganized lists.
Solution Approach 2:
The patent introduces an intelligent intermediary system that acts as a mediator between the user and the content collection. This intermediary automatically categorizes and positions content based on multiple criteria including content type, user preferences, and contextual information, thereby facilitating efficient discovery without requiring users to navigate through raw, unorganized data.
3Difficulty of detecting and measuring
If text-based search is used to help alleviate complexity, then users can search by title, but such searches are of little use unless the consumer already knows exactly what he or she is looking for
Solution Approach 1:
The system provides self-service browsing by automatically organizing and highlighting relevant content based on user context, preferences, and behavior patterns. Users don't need to formulate specific search queries; the system presents curated content that matches their interests, allowing them to discover content they might not have known to search for explicitly.
Solution Approach 2:
The radial visualization dynamically adapts its content arrangement based on user interactions, preferences, and context. The system continuously adjusts the positioning and highlighting of content items, transforming from a static search interface to a dynamic, adaptive display that evolves with user behavior and provides increasingly personalized results.
Data Source
AI summary
One embodiment of the present invention provides a system for browsing a collection of metadata to locate media content associated with an item of metadata. The system operates by receiving a selection of an affinity from a user, wherein the affinity specifies a baseline preference of the user. Next, the system determines a value for each item of metadata in the collection of metadata that specifies how well each item of metadata fits the affinity. Finally, the system arranges the collection of metadata in a view, so that items of metadata with similar values are arranged in close proximity within the view, and so that items of metadata with dissimilar values are not arranged in close proximity within the view.