Announcing the release of my Bridgetown plugin to automatically relate posts!
I’m excited to share something I’ve been working on that I believe will make managing your Bridgetown static blogs a whole lot easier and more effective. Introducing my new plugin: bridgetown-related-posts!
What Is It?
This plugin leverages the power of TF-IDF (Term Frequency-Inverse Document Frequency) and cosine similarity to automatically add related posts to your blog entries.
Gone are the days of manually updating and curating related posts for each new article you publish. With the plugin, the most relevant and similar content is automatically linked, ensuring your readers have easy access to more of your great content.
Why Did I Create This?
As a developer and marketer, I know firsthand the importance of keeping readers engaged and on your site. Manually linking related posts can be tedious and often inconsistent. I wanted a solution that could intelligently and accurately connect similar posts without requiring extra work each time I publish something new. That’s where the idea for this plugin came from.
How Does It Work?
bridgetown-related-posts analyses the content of your posts using TF-IDF, a statistical measure used to evaluate the importance of a word in a document relative to a collection of documents. By calculating the cosine similarity between the vectors of different posts, the plugin determines which posts are most similar to each other. This ensures that the related posts displayed are genuinely relevant and valuable to your readers.
Key Features
- Automatic Updates: Once the plugin is installed, related posts are generated and updated automatically. No more manual curation!
- Accurate Relevance: By using TF-IDF and cosine similarity, the plugin ensures that the related posts are genuinely similar in content.
- Seamless Integration: The plugin is designed to integrate smoothly with your existing BridgetownRB site.
Get Started
You can find the plugin on GitHub: bridgetown-related-posts. The repository includes detailed installation and usage instructions to help you get started quickly.
As always, I’m open to feedback and contributions. If you have any questions, suggestions, or issues, please feel free to reach out or open an issue on GitHub.
Regards
Matt