Contextual Similarity Measures for Object Retrieval
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Solution Overview
Problem
Existing comparison measures do not provide a quantitative assessment of similarity or difference between objects in a specific context, which is essential for applications like information processing, image retrieval, and clustering, as they fail to indicate whether objects are comparable in a given environment.
Innovation Solution
A quantitative contextual comparison module that maximizes or minimizes a comparison function with respect to a weighting parameter, combining the first object and the context, allowing for a quantitative comparison value to be output based on the parameter's value, using existing non-contextual comparison operators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing comparison measures are used, then relative comparisons can be performed, but quantitative assessment of similarity in a specific context cannot be provided
Solution Approach 1:
The patent introduces a contextual comparison measure that modifies the standard comparison function by incorporating a context parameter. The measure computes similarity between objects relative to a given context, allowing the comparison to adapt to different domains or settings. This is achieved by adjusting the comparison function to include contextual information, thereby providing quantitative assessment that is both precise and contextually adaptable.
2Ease of operation
If non-contextual comparison operators are used, then computation is simple, but the ability to determine comparability in a given environment is lost
Solution Approach 1:
The patent introduces context as an intermediary element that mediates between objects being compared. Instead of directly comparing objects using simple operators, the context serves as a mediator that provides the necessary environmental information. This allows the system to determine whether objects are comparable in a given environment while maintaining computational simplicity through the use of existing comparison operators applied to contextualized object representations.
Data Source
AI summary
A method of comparing first and second objects in a context comprises: maximizing or minimizing a quantitative comparison of the first object and a mixture of the second object and the context respective to a weighting parameter that controls the mixture; and outputting a comparison value based on the value of the weighting parameter determined by the maximizing or minimizing.