May 09, 2023
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Service categories
Service Lines
Design
DevOps
Web Development
Domain focus
Advertising & Marketing
Programming language
JavaScript
PHP
Python
Frameworks
Angular.js
Laravel
Node.js
CMS solutions
WordPress
Subcategories
Design
User Experience
DevOps
Docker
Jenkins
Challenge
A startup based in Illinois sought to create a highly personalized WordPress plugin for bloggers. Their goal was to incorporate the capabilities of Google Search Console and natural language AI to optimize blog articles. One of the challenging aspects of the plugin was to generate a list of related posts for each blog post. The system was required to review thousands of posts and recommend the most suitable matches. This process had to be carried out on a daily basis to ensure that the related posts list for each blog post remained current.
A startup based in Illinois sought to create a highly personalized WordPress plugin for bloggers. Their goal was to incorporate the capabilities of Google Search Console and natural language AI to optimize blog articles. One of the challenging aspects of the plugin was to generate a list of related posts for each blog post. The system was required to review thousands of posts and recommend the most suitable matches. This process had to be carried out on a daily basis to ensure that the related posts list for each blog post remained current.
Solution
To leverage the benefits of various technologies and break down the work into smaller, more manageable portions, we developed the project using a microservices architecture. For generating related posts, we utilized NLTK and scikit-learn. Additionally, we accelerated the generation process by utilizing an AWS Lambda function. We adhered to WordPress standards when creating the plugin updater module, ensuring that the WP admin receives a notification as soon as a new version of the plugin is available. To handle background tasks that do not require user interaction, we incorporated AWS SQS to manage the queue.
For deploying the API, we utilized GitHub Actions, while AWS Amplify was used for app deployment.
To leverage the benefits of various technologies and break down the work into smaller, more manageable portions, we developed the project using a microservices architecture. For generating related posts, we utilized NLTK and scikit-learn. Additionally, we accelerated the generation process by utilizing an AWS Lambda function. We adhered to WordPress standards when creating the plugin updater module, ensuring that the WP admin receives a notification as soon as a new version of the plugin is available. To handle background tasks that do not require user interaction, we incorporated AWS SQS to manage the queue.
For deploying the API, we utilized GitHub Actions, while AWS Amplify was used for app deployment.
Results
The client was able to successfully develop and launch a highly personalized WordPress plugin for bloggers that incorporated the capabilities of Google Search Console and natural language AI to optimize blog articles. The client was pleased with the outcome of the project, which met their goal of developing a highly personalized WordPress plugin for bloggers, and has since received positive feedback from their customers.
The client was able to successfully develop and launch a highly personalized WordPress plugin for bloggers that incorporated the capabilities of Google Search Console and natural language AI to optimize blog articles. The client was pleased with the outcome of the project, which met their goal of developing a highly personalized WordPress plugin for bloggers, and has since received positive feedback from their customers.
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