Automated Data Structure Compatibility Scoring via Jaccard Similarity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing mechanisms for determining compatibility between data structures and user devices are inefficient and often require human intervention, making it difficult to automate compatibility decisions at scale.
Innovation Solution
A system and method utilizing modified Jaccard similarity scoring and characteristic-level compatibility calculations to automate compatibility determinations between user devices and data structures, facilitating individually tailored recommendations through personalized circuitry and communications circuitry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human intervention is used to determine compatibility between data structures and user devices, then compatibility determination accuracy is improved, but productivity deteriorates due to the inability to scale automated decisions
Solution Approach 1:
The system enables self-service by automatically determining compatibility between data structures and user devices through characteristic comparisons and Jaccard similarity scoring, eliminating the need for human intervention while maintaining scalability across large numbers of devices and data structures
Solution Approach 2:
The patent replaces the mechanical human decision-making process with an automated computational system that uses characteristic-level compatibility scores and Jaccard similarity algorithms to determine compatibility, thereby achieving both accuracy and scalability
2Productivity
If automated compatibility determination is implemented without characteristic-level analysis, then productivity is improved through automation, but measurement precision deteriorates due to lack of detailed compatibility assessment
Solution Approach 1:
The system segments the compatibility determination process into characteristic-level components, where individual characteristics of data structures and user devices are compared separately to generate characteristic-level compatibility scores, which are then aggregated to produce an overall compatibility determination
Solution Approach 2:
The patent transforms the compatibility assessment by introducing characteristic-level compatibility scores as intermediate parameters, calculated using Jaccard similarity scoring on individual characteristics, which provides detailed granularity while maintaining automated scalability
Data Source
AI summary
Embodiments are disclosed for automated evaluation of compatibility of a data structure with a user device. An example method includes receiving, by communications circuitry, a set of user device characteristics regarding the user device, and retrieving, by the personalization circuitry, a set of data structure characteristics regarding the data structure. The example method further includes calculating, by the personalization circuitry, a set of characteristic-level compatibility scores, and generating, by the personalization circuitry and based on the set of characteristic-level compatibility scores, a compatibility score for the data structure and the user device. Subsequently, the example method includes generating, by an aggregator and using the generated compatibility score, an indication of relative compatibility of the data structure for the user device, and causing transmission, by communications circuitry, of a control signal to the user device based on the indication of relative compatibility. Corresponding apparatuses and computer program products are also provided.