Unit Group Dictionary for Personalized Object Search
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Solution Overview
Problem
Current search and interaction methods with electronic devices limit the ability to search for, share, and experience objects beyond their descriptive information, as they rely on keywords and do not account for individual perspectives or contexts.
Innovation Solution
The system allows users to create object identifiers with annotations that reflect their personal contexts, enabling the formation of unit groups and relationships between objects and users with similar interests, which can be used to manage, search, and share objects by organizing them into sets based on these contexts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If keyword-based search methods are used, then search simplicity is maintained, but search effectiveness and personalization are limited
Solution Approach 1:
The patent segments the search system into multiple components: keyword matching, user profile analysis, and contextual information processing. Each component handles specific aspects of the search, allowing the system to maintain simplicity while incorporating personalization without overwhelming complexity in any single area.
Solution Approach 2:
The patent introduces an intermediary layer that processes both keywords and user-specific contextual information. This intermediary synthesizes multiple data sources (search terms, user profiles, historical data) into unified search results, enabling personalization without requiring users to directly manage complex personalization settings.
2Adaptability or versatility
If unit groups and relationships are established based on multiple contexts, then object discovery capability is improved, but system complexity increases
Solution Approach 1:
The patent divides the complex relationship mapping into manageable segments by creating unit groups that categorize objects based on specific contexts. Each unit group represents a discrete contextual dimension (e.g., user interests, object attributes), allowing the system to handle complexity in organized, modular units rather than as a monolithic structure.
Solution Approach 2:
The patent adds contextual dimensions to the object relationship model beyond traditional keyword matching. By incorporating multiple contextual layers (user profiles, object attributes, interaction history), the system transforms a flat search structure into a multi-dimensional space where objects can be discovered through various contextual pathways, increasing versatility without linearly increasing complexity.
3Measurement precision
If annotations reflecting personal contexts are collected, then search personalization is enhanced, but data processing requirements increase
Solution Approach 1:
The patent extracts only the most relevant contextual information from user annotations and interactions, rather than processing all available data equally. By identifying and extracting key personalization signals (preferred categories, frequently accessed objects, stated interests), the system achieves high personalization accuracy while minimizing the volume of data requiring intensive processing.
Solution Approach 2:
The patent implements partial processing of annotation data by focusing on the most impactful contextual factors for personalization. Rather than fully analyzing every annotation in detail, the system processes sufficient data to achieve effective personalization results, applying deeper analysis only where it most significantly impacts search quality, thus balancing precision with processing efficiency.
Data Source
AI summary
Described are systems and methods for establishing a unit group dictionary based on user provided annotations. The unit group dictionary may be used to identify relationships between multiple items in a corpus. Those relationships may facilitate the display of object identifiers and/or other aspects used and/or provided by the object management service.