Smart Tag Prioritization for Object Retrieval
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Solution Overview
Problem
Users face challenges in quickly finding specific objects across multiple devices and cloud storage due to unhelpful file names and lack of effective retrieval mechanisms, especially for non-data objects like pictures and videos.
Innovation Solution
The implementation of smart tags generated based on user events, using metadata and contextual data, with a tagging profile that prioritizes tag creation based on user preferences and behaviors, allowing for efficient and user-specific smart tag generation and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If smart tags are generated for all user objects, then object retrieval efficiency is improved, but storage and processing resources are excessively consumed
Solution Approach 1:
The patent applies local quality by making tag generation selective rather than universal. The system analyzes user behavior patterns and generates tags only for objects that match specific criteria (e.g., objects the user interacts with frequently or objects in specific contexts). This ensures storage resources are consumed only where they provide retrieval value, rather than uniformly across all objects.
Solution Approach 2:
The system implements partial action by generating tags for only a subset of objects rather than all objects. The tagging priority mechanism determines which objects receive tags based on user preferences and behavior patterns, performing just enough tagging to improve retrieval efficiency without the excessive resource consumption that would result from universal tagging.
2Productivity
If smart tags are generated for all user objects, then object retrieval efficiency is improved, but processing resources are excessively consumed
Solution Approach 1:
The system applies local quality by concentrating processing resources on generating tags only for high-priority objects identified through user behavior analysis. Instead of uniformly processing all objects, the system selectively applies tagging efforts to objects where users are most likely to benefit from improved retrieval, thereby reducing overall processing resource consumption.
Solution Approach 2:
The patent implements partial action by performing tag generation only for a prioritized subset of objects rather than all objects. The tagging priority mechanism filters objects based on user preferences and behavior patterns, ensuring processing resources are spent only on partial tagging operations that deliver maximum retrieval efficiency improvement with minimum resource expenditure.
3Measurement precision
If user-specific tagging profiles are created, then tag relevance is improved, but device complexity is increased
Solution Approach 1:
The system applies preliminary action by pre-analyzing user behavior patterns and preferences to create tagging profiles before actual tag generation occurs. This preliminary profiling phase captures user characteristics and object interaction patterns, which then guide subsequent tag generation to ensure high relevance without requiring complex real-time analysis during tagging operations.
Solution Approach 2:
The patent implements copying by creating simplified tagging profiles that replicate essential user preferences and behavior patterns. Rather than maintaining complex user models, the system creates condensed profile representations that capture the necessary information for generating relevant tags, thereby achieving high tag relevance with reduced system complexity.
Data Source
AI summary
An aspect provides a method, including: accessing, using a processor, a store of historical user object event information; building, using the processor, a tagging profile based on the store of historical user object event information; determining, using the processor, a new user object event; and determining, using the processor, a priority for tag generation for the new object event using the tagging profile. Other aspects are described and claimed.