Automated Collection Metadata Generation via Attribute Distribution Analysis
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Solution Overview
Problem
Existing methods for annotating large groups of visual images using average image characteristics are not meaningful, making them less suitable for browsing and searching in hierarchically organized systems.
Innovation Solution
A method that analyzes the distribution of metadata attributes across content items, selects relevant attribute values, and generates metadata for collections with minimal human intervention, allowing for efficient representation and location of content items within a system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If average value of image characteristics is used for annotation, then annotation can be generated automatically, but the annotation becomes less meaningful and suitable for browsing and searching
Solution Approach 1:
The patent extracts only the most representative and meaningful attribute values from the content items in a collection, rather than using all attributes or average values. This selective extraction ensures that the generated annotation captures the essential characteristics of the collection while remaining meaningful for browsing and searching.
Solution Approach 2:
The patent applies different selection criteria to different attributes based on their distribution characteristics. By analyzing the distribution of each attribute and applying locally optimized selection strategies, the system generates annotations that are meaningful for the specific characteristics of each attribute rather than applying a uniform averaging approach.
2Loss of information
If all attribute values are included in metadata, then completeness is improved, but expressiveness and conciseness deteriorate
Solution Approach 1:
The system extracts only the most representative attribute values that best characterize the collection. By selecting a limited set of meaningful attributes rather than including all possible attributes, the patent achieves a balance between completeness and conciseness, making the metadata both informative and manageable.
Solution Approach 2:
Instead of including all attribute values (excessive action), the patent selectively includes only the necessary subset of attributes that provide the most value for representing the collection. This partial action approach avoids information overload while maintaining essential completeness.
3Device complexity
If representative content item is selected for annotation, then annotation generation is simplified, but accuracy and expressiveness of collection representation deteriorate
Solution Approach 1:
The patent segments the collection analysis into two parts: first identifying the most representative attributes through distribution analysis, then selecting specific attribute values for those attributes. This segmentation allows the system to maintain simplicity while improving accuracy by focusing computational effort on the most meaningful characteristics rather than trying to represent all items equally.
Solution Approach 2:
The patent introduces distribution analysis as an intermediary step between selecting a representative item and generating the annotation. This intermediary process analyzes attribute distributions across the collection to identify the most representative values, thereby improving accuracy without significantly increasing overall system complexity.
Data Source
AI summary
A method of automatically generating metadata for association with a collection of content items accessible to a system (1) for processing data included in the content items, includes obtaining sets of metadata associated with the content items individually, each set of metadata including at least one attribute value associated with the content item. At least one distribution of values of an attribute over the sets of metadata associated with the respective content items is analyzed. At least one attribute value is selected in dependence on the analysis. The selected attribute value(s) are processed to generate the metadata for association with the collection, and the generated metadata are made available to the system (1) for processing data included in the content items in connection with an identification of the collection of content items.