Concept Indexing for Cross-Content Association
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Solution Overview
Problem
Users of digital content items face challenges in efficiently exploring and relating concepts across various content items on electronic devices, as existing technologies do not effectively facilitate the association and search for interconnected ideas within a unified index.
Innovation Solution
Electronic devices implement techniques to allow users to associate concepts within an index, enabling the linking of concepts across different content items, allowing for enhanced search functionality that returns results with specified proximity, tailored to individual user preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually search for concepts across multiple content items, then they can find information about interesting concepts, but the process is time-consuming and inefficient
Solution Approach 1:
The system pre-processes content items to identify and extract concepts, creating a structured index of concepts and their relationships before users need to search. This preliminary organization of information allows users to quickly access concept associations without manually searching through content items, directly resolving the time efficiency contradiction
2Loss of information
If the system provides detailed information about concept associations, then users can understand interrelations between concepts, but the interface becomes complex and overwhelming
Solution Approach 1:
The system segments the display of concept association information into multiple hierarchical levels: basic associations, detailed relationships, and contextual connections. Users can progressively access deeper levels of information as needed, preventing information overload while maintaining comprehensive concept relationship data availability
Solution Approach 2:
The interface dynamically adapts its complexity based on user interactions and selections. When users select concepts, the system dynamically presents relevant association information at appropriate detail levels, adjusting the information density and structural complexity to match user needs without creating a permanently complex interface
3Adaptability or versatility
If the system indexes all concepts from all content items, then comprehensive search coverage is achieved, but the index size and processing requirements increase
Solution Approach 1:
The system applies different indexing strategies to different concepts based on their characteristics, frequency, and importance. High-frequency or important concepts receive more detailed indexing with multiple associations, while less important concepts receive simplified indexing. This selective approach maintains comprehensive search coverage while optimizing index structure complexity
Data Source
AI summary
Techniques for associating concepts found within content items rendered by electronic devices. By associating concepts in this manner, a user of an electronic device is able to view how these concepts interrelate with one another across various content items stored on or accessible by the electronic device. For instance, a user may associate a first concept with a second concept in an index of the electronic device. Thereafter, the user may conduct a search for the first concept and, in response, the electronic device may reference the index and determine that this first concept is in fact associated with the second concept. As such, the electronic device may return results that include both the first and second concepts, possibly within a certain specified distance of one another within a content item. The user is therefore able to see how the first concept and the second concept interrelate with one another.