Selectable Item Availability Output for No-Recode Portal Updates
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Solution Overview
Problem
Organizations face challenges in quickly updating and revising content and configurations of purchasing portals without recoding, and users encounter difficulties in purchasing multiple products without repetitive data entry.
Innovation Solution
A computing platform with machine learning algorithms integrates with switchboard and content output control platforms to generate and update selectable item availability outputs, allowing real-time configuration and content modifications via user interfaces, reducing the need for recoding and minimizing data reentry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional portal systems are used for purchasing products, then users can access product information and make purchases, but updating and revising content and configurations requires recoding the portal, which is time-consuming and inefficient
Solution Approach 1:
The patent segments the portal system into distinct functional components: a machine learning model that generates selectable item availability outputs, a configuration system that manages portal settings, and a content management system that handles product information. This segmentation allows each component to be updated independently without recoding the entire portal, thereby improving content and configuration update efficiency while reducing the time required for modifications.
2Ease of operation
If portal content and configurations are updated frequently to maintain purchasing efficiency, then user experience improves, but the complexity of managing updates and recoding increases
Solution Approach 1:
The patent implements a self-service mechanism where the machine learning model automatically generates selectable item availability outputs based on input data, eliminating the need for manual recoding or complex configuration updates. The system self-adjusts to maintain purchasing efficiency by processing user inputs and generating appropriate product recommendations, thereby improving ease of operation while reducing portal maintenance complexity.
3Productivity
If users enter personal information multiple times to purchase multiple products, then each purchase can be processed individually, but user time and effort increase
Solution Approach 1:
The patent applies preliminary action by having users enter their personal information once at the beginning of the purchasing process. The machine learning model then stores this information and automatically retrieves it for subsequent product selections, eliminating the need for repeated information entry. This approach improves multiple product purchasing efficiency while reducing the time users spend on data entry.
Data Source
AI summary
Aspects of the disclosure relate to enhanced selectable item availability processing systems with improved content and configuration update capability and enhanced selectable item availability output determinations. A computing platform may receive a selectable item availability configuration output comprising a configuration update to the selectable item availability output and a selectable item availability content output comprising a content update to the selectable item availability output. Based on the selectable item availability configuration output and the selectable item availability content output, the computing platform may generate an updated selectable item availability output. The computing platform may receive a request to access the selectable item availability output. The computing platform may generate one or more commands to cause display of the updated selectable item availability output and may send, to a user device, the updated selectable item availability output along with the one or more commands.