Intelligent Content Item Importing with Automated Grouping
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Solution Overview
Problem
Users face challenges in organizing large quantities of digital content items such as photos, documents, and videos due to the lack of effective automated organization tools, leading to increased time spent on manual organization and inefficient use of existing photo management applications.
Innovation Solution
A content item import processor compares new content items to existing organizational units based on metadata and similarity thresholds, automatically adding them to matching groups or creating new groups if no match is found, with user feedback used to improve matching algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If photos are organized manually by users, then organization accuracy is improved, but time consumption increases significantly
Solution Approach 1:
The system automatically analyzes imported photos and organizes them into albums without requiring user intervention. The photo management application performs self-service organization by comparing photo characteristics (such as metadata, content analysis) with existing album criteria, thereby eliminating manual sorting time while maintaining organization accuracy.
Solution Approach 2:
The patent replaces manual mechanical sorting operations with automated computational analysis. The system uses algorithms to analyze photo content, extract features, and match photos to appropriate albums automatically, substituting human manual organization with machine-based automated processing.
2Loss of time
If photos are organized by import event automatically, then time consumption is reduced, but organization meaningfulness deteriorates
Solution Approach 1:
The system replaces simple import-event-based automatic organization with intelligent content-based organization. Algorithms analyze photo content, metadata, and characteristics to automatically determine the most meaningful album assignments, going beyond mere import timing to provide semantically meaningful organization.
Solution Approach 2:
The patent changes the organizing parameters from simple import timestamp to multiple photo attributes including content analysis results, metadata fields, and similarity metrics. By changing these parameters, the system achieves both automation and meaningful organization simultaneously.
3Extent of automation
If advanced organization algorithms are implemented, then organization intelligence is improved, but system complexity increases
Solution Approach 1:
The patent segments the organization process into distinct modular components: photo import module, content analysis module, similarity calculation module, album matching module, and user feedback module. Each module performs a specific function independently, making the complex system manageable and maintainable while achieving high organization intelligence.
Solution Approach 2:
The system introduces intermediary components such as photo profiles (stored in databases) that act as intermediaries between raw photo data and organization decisions. These profiles contain extracted features and characteristics, serving as a buffer that simplifies the matching process between photos and albums.
4Measurement precision
If user feedback is collected and processed, then matching accuracy is improved, but processing time increases
Solution Approach 1:
The system performs preliminary organization automatically upon photo import, providing immediate results to the user. User feedback is then processed in subsequent iterations to refine and improve the matching algorithms over time, rather than blocking the initial organization process.
Solution Approach 2:
The organization system operates continuously, with the matching algorithm running automatically on each import. User feedback processing occurs in the background or in subsequent batches, allowing the system to maintain continuous useful organization action while gradually improving accuracy through feedback incorporation.
Data Source
AI summary
Systems, methods, and computer-readable storage media for importing a new content item, such as a photo, document, video, email, or application, into a content item repository. A content item repository can contain a set of existing content item groups, and each content item group can include at least one content item. The system can calculate a profile for a new content item to be imported. Upon determining, based on the calculated profile, that the new content item exceeds a similarity threshold for an existing content item group, the system can insert the new content item into the content item group. Upon determining, based on the calculated profile, that the new content item does not exceed the similarity threshold for any existing content item group, the system can create a new content item group and insert the new content item therein.