Cognitive Content Matching for Platform Selection
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Solution Overview
Problem
Existing content management tools fail to provide insightful guidance on which platform is most relevant and appropriate for uploading content, leading to insecure, costly, and sub-optimally performed content uploads due to inappropriate platform selection.
Innovation Solution
A computing device and method that recognize features of content to be shared, determine relevant platforms for access by other users, and select the most suitable platforms for storage based on these features, utilizing a cognitive analyzer with components like feature recognizers, platform selectors, and historical analyzers to ensure secure and efficient content distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If content is uploaded to multiple platforms using conventional tools, then content accessibility is improved, but security is worsened due to inappropriate platform selection
Solution Approach 1:
The system enables self-service by automatically analyzing content features and selecting appropriate platforms without human intervention. The cognitive analyzer independently evaluates content characteristics and matches them with suitable platforms, eliminating manual platform selection errors and ensuring secure content distribution.
Solution Approach 2:
The system implements feedback mechanisms where the cognitive analyzer continuously learns from content analysis and platform performance data. This feedback loop improves the accuracy of content-platform matching over time, enhancing security by reducing inappropriate platform selections through iterative optimization.
2Adaptability or versatility
If content is uploaded to inappropriate platforms, then platform versatility is improved, but operational latency is worsened
Solution Approach 1:
The system performs preliminary action by pre-analyzing content features and pre-determining optimal platform selections before actual content upload. The cognitive analyzer prepares platform recommendations in advance based on content characteristics, enabling faster execution during the actual upload operation and reducing operational latency.
3Productivity
If content is uploaded to multiple platforms without guidance, then content distribution is improved, but power consumption is worsened
Solution Approach 1:
The system applies local quality by tailoring platform selection to the specific characteristics of each content item rather than uniformly distributing content across all platforms. The cognitive analyzer evaluates individual content features and selects only the most appropriate platforms, reducing unnecessary uploads and associated power consumption while maintaining effective content distribution.
4Ease of operation
If conventional content management tools are used, then ease of operation is improved, but manufacturing precision (content placement accuracy) is worsened
Solution Approach 1:
The system maintains ease of operation while improving precision by implementing self-service automation. Users simply initiate content upload without specifying target platforms, and the cognitive analyzer automatically handles the complex analysis and selection process, achieving both operational simplicity and accurate content placement.
Data Source
AI summary
Methods and systems may provide for technology to recognize features of current content to be shared by a current user, determine a plurality of platforms that allow access to data by other users and select one or more of the plurality of platforms to store the current content based on the recognized features.